Skip to main content

Full text of "Flash Boys. A Wall Street Revolt"

See other formats







ISBN 978-O-393-24466-3 

USA $27.95 
CAN. $32.95 

Four years after his #1 bestseller The Big 
Short , Michael Lewis returns to Wall Stree c 
report on a high-tech predator stalking the 
equity markets. 

Flash Boys is about a small group of Wall 
Street guys who figure out that the U.S. stock 
market has been rigged for the benefit of 
insiders and that, post-financial crisis, the 
markets have become not more free but less, 
and more controlled by the big Wall Street 
banks. Working at different firms, they come 
to this realization separately; but after they 
discover one another, the flash boys band 
together and set out to reform the financial 
markets. This they do by creating an exchange 
in which high-frequency trading — source of 
the most intractable problems — will have no 
advantage whatsoever. 

The characters in Flash Boys are fabulous, 
each completely different from what you 
think of when you think “Wall Street guy.” 
Several have walked away from jobs in the 
financial sector that paid them millions of 
dollars a year. From their new vantage point 
they investigate the big banks, the world’s 
stock exchanges, and high-frequency trading 
firms as they have never been investigated, 
and expose the many strange new ways that 
Wall Street generates profits. 

The light that Lewis shines into the darkes’ 
corners of the financial world may not be 

(continued on back flap) 

APR 2014 




The Big Short 
Home Game 
The Blind Side 

The Neu> New Thing 
Pacific Rift 
The Money Culture 
Liar’s Poker 







New York | London 

Copyright © 2014 by Michael Lewis 
All rights reserved 

Printed in the United States of America 
First Edition 

For information about permission to reproduce selections from this book, 
write to Permissions, W.W. Norton & Company, Inc., 

500 Fifth Avenue, New York, NY 10110 

For information about special discounts for bulk purchases, please contact 
W.W. Norton Special Sales at or 800-233-4830 

Manufacturing by Courier Westford 
Book design by Chris Welch Design 
Production manager: Julia Druskin 

ISBN 978-0-393-24466-3 

W.W. Norton & Company, Inc. 

500 Fifth Avenue, New York, N.Y. 10110 

W.W. Norton & Company Ltd. 

Castle House, 75/76 Wells Street, London W 1 T 3QT 


A man got to have a code. 
— Omar Little 






















Acknowledgments 273 





I suppose this book started when I first heard the story ot Ser- 
gey Aleynikov, the Russian computer programmer who had 
worked for Goldman Sachs and then, in the summer of 2009, 
after he’d quit his job, was arrested by the FBI and charged by 
the United States government with stealing Goldman Sachs’s 
computer code. I’d thought it strange, after the financial crisis, 
in which Goldman had played such an important role, that the 
only Goldman Sachs employee who had been charged with any 
sort of crime was the employee who had taken something from 
Goldman Sachs. I’d thought it even stranger that government 
prosecutors had argued that the Russian shouldn’t be freed on 
bail because the Goldman Sachs computer code, in the wrong 
hands, could be used to “manipulate markets in unfair ways.” 
(Goldman’s were the right hands? If Goldman Sachs was able to 
manipulate markets, could other banks do it, too?) But maybe 
the strangest aspect of the case was how difficult it appeared to 
be — for the few who attempted — to explain what the Russian 



had done. I don’t mean only what he had done wrong: I mean 
what he had done. His job. He was usually described as a “high- 
frequency trading programmer,” but that wasn’t an explanation. 
That was a term of art that, in the summer of 2009, most people, 
even on Wall Street, had never before heard. What was high- 
frequency trading? Why was the code that enabled Goldman 
Sachs to do it so important that, when it was discovered to have 
been copied by some employee, Goldman Sachs needed to call 
the FBL It this code was at once so incredibly valuable and so 
dangerous to financial markets, how did a Russian who had 
worked for Goldman Sachs for a mere two years get his hands 
on it? 

At some point I went looking for someone who might answer 
those questions. My search ended in a room looking out at the 
World Trade Center site, at One Liberty Plaza. In this room 
were gathered a small army of shockingly well-informed people 
from every corner ot Wall Street — big banks, the major stock 
exchanges, and high-frequency trading firms. Many of them had 
left high-payingjobs to declare war on Wall Street, which meant, 
among other things, attacking the very problem that the Russian 
computer programmer had been hired by Goldman Sachs to 
create. In the bargain they’d become experts on the questions 
I sought answers to, along with a lot of other questions I hadn’t 
thought to ask. These, it turned out, were tar more interesting 
than I expected them to be. 

I didn t start out with much interest in the stock market — 
though, like most people, I enjoy watching it go boom and crash. 
When it crashed on October 19, 1987, I happened to be hovering 
around the fortieth floor of One New York Plaza, the stock market 
trading and sales department of my then employer, Salomon 
Brothers. That was interesting. If you ever needed proof that even 



Wall Street insiders have no idea what’s going to happen next on 
Wall Street, there it was. One moment all is well; the next, the 
value of the entire U.S. stock market has fallen 22.61 percent, and 
no one knows why. During the crash, some Wall Street brokers, 
to avoid the orders their customers wanted to place to sell stocks, 
simply declined to pick up their phones. It wasn’t the first time 
that Wall Street people had discredited themselves, but this time 
the authorities responded by changing the rules — making it easier 
for computers to do the jobs done by those imperfect people. The 
1987 stock market crash set in motion a process — weak at first, 
stronger over the years — that has ended with computers entirely 
replacing the people. 

Over the past decade, the financial markets have changed too 
rapidly for our mental picture of them to remain true to lite. The 
picture I’ll bet most people have of the markets is still a picture a 
human being might have taken. In it, a ticker tape runs across the 
bottom of some cable TV screen, and alpha males in color-coded 
jackets stand in trading pits, hollering at each other. That picture 
is dated; the world it depicts is dead. Since about 2007, there 
have been no thick-necked guys in color-coded jackets standing 
in trading pits; or, if they are, they’re pointless. There are still 
some human beings working on the floor of the New York Stock 
Exchange and the various Chicago exchanges, but they no longer 
preside over any financial market or have a privileged view inside 
those markets. The U.S. stock market now trades inside black 
boxes, in heavily guarded buildings in New Jersey and Chicago. 
What goes on inside those black boxes is hard to say — the ticker 
tape that runs across the bottom of cable TV screens captures 
only the tiniest fraction of what occurs in the stock markets. The 
public reports of what happens inside the black boxes are fuzzy 
and unreliable — even an expert cannot say what exactly happens 



inside them, or when it happens, or why. The average investor has 
no hope of knowing, of course, even the little he needs to know. 
He logs onto his TD Ameritrade or E*Trade or Schwab account, 
enters a ticker symbol of some stock, and clicks an icon that says 
“Buy”: Then what? He may think he knows what happens after 
he presses the key on his computer keyboard, but, trust me, he 
does not. If he did, he’d think twice before he pressed it. 

The world clings to its old mental picture of the stock market 
because it’s comforting; because it’s so hard to draw a picture of 
what has replaced it; and because the few people able to draw it 
for you have no interest in doing so. This book is an attempt to 
draw that picture. The picture is built up from a bunch of smaller 
pictures — of post-crisis Wall Street; of new kinds of financial 
cleverness; of computers, programmed to behave impersonally in 
ways that the programmer himself would never do personally; of 
people, coming to Wall Street with one idea of what makes the 
place tick only to find that it ticks rather differently than they had 
supposed. One of these people — a Canadian, of all things — stands 
at the picture’s center, organizing the many smaller pictures into 
a coherent whole. His willingness to throw open a window on 
the American financial world, and to show people what it has 
become, still takes my breath away. 

As does the Goldman high-frequency trading programmer 
arrested for stealing Goldman’s computer code. When he worked 
for Goldman Sachs, Sergey Aleynikov had a desk on the forty- 
second floor of One New York Plaza, the site of the old Salomon 
Brothers trading floor, two floors above the place I’d once watched 
the stock market crash. He hadn’t been any more interested in 
staying in that building than 1 had been and, in the summer of 
2009, had left to seek his fortune elsewhere. On July 3, 2009, he 
was on a flight from Chicago to Newark, New Jersey, blissfully 



unaware of his place in the world. He had no way of knowing 
what was about to happen to him when he landed. Then again, 
he had no idea how high the stakes had become in the financial 
game he’d been helping Goldman Sachs to play. Oddly enough, 
to see the magnitude of those stakes, he had only to look out the 
window of his airplane, down on the American landscape below. 



B y the summer of 2009 the line had a life of its own, and two 
thousand men were digging and boring the strange home 
it needed to survive. Two hundred and five crews of eight 
men each, plus assorted advisors and inspectors, were now rising 
early to figure out how to blast a hole through some innocent 
mountain, or tunnel under some riverbed, or dig a trench beside 
a country road that lacked a roadside- — all without ever answering 
the obvious question: Why? The line was just a one-and-a-half- 
inch-wide hard black plastic tube designed to shelter four hundred 
hair-thin strands of glass, but it already had the feeling of a living 
creature, a subterranean reptile, with its peculiar needs and wants. 
It needed its burrow to be straight, maybe the most insistently 
straight path ever dug into the earth. It needed to connect a data 
center on the South Side of Chicago* to a stock exchange in north- 
ern New Jersey. Above all, apparently, it needed to be a secret. 

The principal data center was later moved to Aurora, Illinois, outside Chicago. 



The workers were told only what they needed to know. They 
tunneled in small groups apart from each other, with only a 
local sense ot where the line was coming from or where it was 
going to. They were specifically not told of the line’s purpose — 
to make sure they didn’t reveal that purpose to others. “All the 
time, people are asking us, ‘Is this top secret? Is it the govern- 
ment? I just said, Yeah, ’ said one worker. The workers might 
not have known what the line was for, but they knew that it had 
enemies: They all knew to be alert to potential threats. If they 
saw anyone digging near the line, for instance, or noticed any- 
one asking a lot of questions about it, they were to report what 
they’d seen immediately to the head office. Otherwise they were 
to say as little as possible. If people asked them what they were 
doing, they were to say, “Just laying fiber.” That usually ended 
the conversation, but if it didn’t, it didn’t really matter. The con- 
struction crews were as bewildered as anyone. They were used 
to digging tunnels that connected cities to other cities, and peo- 
ple to other people. This line didn’t connect anyone to anyone 
else. Its sole purpose, as far as they could see, was to be as straight 
as possible, even if that meant they had to rocksaw through a 
mountain rather than take the obvious way around it. Why? 

Right up until the end, most workers didn’t even ask the 
question. The country was flirting with another depression and 
they were just happy for the work. As Dan Spivey said, “No one 
knew why. People began to make their reasons up.” 

Spivey was the closest thing the workers had to an explanation 
for the line, or the bed they were digging for it. And Spivey was 
by nature tight-lipped, one of those circumspect southerners with 
more thoughts than he cared to share. He’d been born and raised 
in Jackson, Mississippi, and, on those rare occasions he spoke, he 
sounded as if he d never left. He’d just turned forty but was still as 



lean as a teenager, with the face of a Walker Evans tenant farmer. 
After some unsatisfying years working as a stockbroker in Jack- 
son he’d quit, as he put it, “to do something more sporting.” That 
turned out to be renting a seat on the Chicago Board Options 
Exchange and making markets for his own account. Like every 
other trader on the Chicago exchanges, he saw how much money 
could be made trading futures contracts in Chicago against the 
present prices of the individual stocks trading in New York and 
New Jersey. Every day there were thousands of moments when 
the prices were out of whack — when, for instance you could sell 
the futures contract for more than the price of the stocks that 
comprised it. To capture the profits, you had to be fast to both 
markets at once. What was meant by “fast” was changing rapidly. 
In the old days — before, say, 2007 — the speed with which a trader 
could execute had human limits. Human beings worked on the 
floors of the exchanges, and if you wanted to buy or sell anything 
you had to pass through them. The exchanges, by 2007, were 
simply stacks of computers in data centers. The speed with which 
trades occurred on them was no longer constrained by people. 
The only constraint was how fast an electronic signal could travel 
between Chicago and New York — or, more precisely, between 
the data center in Chicago that housed the Chicago Mercantile 
Exchange and a data center beside the Nasdaq’s stock exchange 
in Carteret, New Jersey. 

What Spivey had realized, by 2008, was that there was a big 
difference between the trading speed that was available between 
these exchanges and the trading speed that was theoretically pos- 
sible. Given the speed of light in fiber, it should have been pos- 
sible for a trader who needed to trade in both places at once to 
send his order from Chicago to New York and back in roughly 
12 milliseconds, or roughly a tenth of the time it takes you to 



blink your eyes, if you blink as fast as you can. (A millisecond 
is one thousandth of a second.) The routes offered by the vari- 
ous telecom carriers — Verizon, AT&T, Level 3, and so on — were 
slower than that, and inconsistent. One day it took them 17 mil- 
liseconds to send an order to both data centers; the next, it took 
them 16 milliseconds. By accident, some traders had stumbled 
across a route controlled by Verizon that took 14.65 milliseconds. 
“The Gold Route,” the traders called it, because on the occasions 
you happened to find yourself on it you were the first to exploit 
the discrepancies between prices in Chicago and prices in New 
York. Incredibly to Spivey, the telecom carriers were not set up 
to understand the new demand for speed. Not only did Verizon 
fail to see that it could sell its special route to traders for a fortune; 
Verizon didn’t even seem aware it owned anything of special 
value. “You would have to order up several lines and hope that 
you got it,” says Spivey. “They didn’t know what they had.” As 
late as 2008, major telecom carriers were unaware that the finan- 
cial markets had changed, radically, the value of a millisecond. 

Upon closer investigation, Spivey saw why. He went to Wash- 
ington, DC, and got his hands on the maps of the existing fiber 
cable routes running from Chicago to New York. They mostly 
followed the railroads and traveled from big city to big city. 
Leaving New York and Chicago, they ran fairly straight toward 
each other, but when they reached Pennsylvania they began to 
wiggle and bend. Spivey studied a map of Pennsylvania and saw 
the main problem: the Allegheny Mountains. The only straight 
line running through the Alleghenies was the interstate high- 
way, and there was a law against laying fiber along the interstate 
highway. The other roads and railroads zigzagged across the state 
as the landscape permitted. Spivey found a more detailed map of 
Pennsylvania and drew his own line across it. “The straightest 



path allowed by law,” he liked to call it. By using small paved 
roads and dirt roads and bridges and railroads, along with the 
occasional private parking lot or front yard or cornfield, he 
could cut more than a hundred miles oft the distance traveled by 
the telecom carriers. What was to become Spivey’s plan, then his 
obsession, began with an innocent thought: I’d like to see how 
much faster someone would be if they did this. 

In late 2008, with the global financial system in turmoil, 
Spivey traveled to Pennsylvania and found a construction guy 
to drive him the length of his idealized route. For two days they 
rose together at five in the morning and drove until seven at 
night. “What you see when you do this,” says Spivey, “is very 
small towns, and very tiny roads with cliffs on one side and a 
sheer rock wall on the other.” The railroads traveling east to 
west tended to tack north and south to avoid the mountains: 
They were of limited use. “Anything that wasn’t absolutely east- 
west that had any kind of curve in it I didn’t like,” Spivey said. 
Small country roads were better for his purposes, but so tightly 
squeezed into the rough terrain that there was no place to lay the 
fiber but under the road. “You’d have to close the road to dig up 
the road,” he said. 

The construction guy with him clearly suspected he might be 
out of his mind. Yet when Spivey pressed him, even he couldn’t 
come up with a reason why the plan wasn’t at least theoretically 
possible. That’s what Spivey had been after: a reason not to do 
it. “I was just trying to find the reason no [telecom] carrier had 
done it,” he says. “I was thinking: Surely I’ll see some road- 
block.” Aside from the construction engineer’s opinion that no 
one in his right mind wanted to cut through the hard Allegheny 
rock, he couldn’t find one. 

That’s when, as he puts it, “I decided to cross the line.” The 



line separated Wall Street guys who traded options on Chicago 
exchanges from people who worked in the county agencies and 
Department of Transportation offices that controlled public 
rights-of-way through which a private citizen might dig a secret 
tunnel. He sought answers to questions: What were the rules 
about laying fiber-optic cable? Whose permission did you need? 
The line also separated Wall Street people from people who 
knew how to dig holes and lay fiber. How long would it take? 
How many yards a day might a crew with the right equipment 
tunnel through rock? What kind of equipment was required? 
What might it cost? 

Soon a construction engineer named Steve Williams, who 
lived in Austin, Texas, received an unexpected call. As Williams 
recalls, “It was from a friend of mine. He said, ‘I have an old 
friend whose cousin is in trouble, and he has some construc- 
tion questions he needs answers to.’ ” Spivey himself then called. 
“This guy gets on the phone,” recalls Williams, “and is ask- 
ing questions about case sizes, and what kind of fiber you use, 
and how would you dig in this ground and under this river.” 
A few months later Spivey called him again — to ask him if he 
would supervise the laying of a fifty-mile stretch of fiber, start- 
ing in Cleveland. “I didn’t know what I was getting into,” said 
Williams. Spivey told him nothing more about the project than 
what he needed to know to lay a single fifty-mile stretch of 
cable. In between, Spivey had persuaded Jim Barskdale, the for- 
mer CEO of Netscape Communications and a fellow native of 
Jackson, to fund what Spivey estimated to be a $300 million 
tunnel. They named the company Spread Networks, though 
they disguised the construction behind shell companies with 
dull names like Northeastern ITS and Job 8. Jim Barksdale’s son, 
David Barksdale, came on board — to cut, as quietly as possible, 



the four hundred or so deals they needed to cut with townships 
and counties in order to be able to tunnel through them. Wil- 
liams then proved so adept at getting the line into the ground 
that Spivey and Barksdale called and asked him to take over the 
entire project. “That’s when they said, ‘Hey, this is going all the 
way to New Jersey,’ ” Williams said. 

Leaving Chicago, the crews had raced across Indiana and 
Ohio. On a good day they were able to lay two to three miles of 
the line in the ground. When they arrived in western Pennsyl- 
vania they hit the rock and the pace slowed, sometimes to a few 
hundred feet a day. “They call it blue rock,” says Williams. “It’s 
hard limestone. And it’s a challenge to get through.” He found 
himself having the same conversation, over and over again, with 
Pennsylvania construction crews. “I’d explain to them that we 
need to go through some mountain, and one after another they 
would say, ‘That’s crazy.’ And I would say, ‘I know that’s crazy, 
but that’s how we’re doing it.’ And they would ask, ‘Why?’ And 
I’d say, ‘It’s more of a customized route to the owner’s wishes.’ ” 
To which they really didn’t have much to say except, “Oh.” 
His other problem was Spivey, who was all over him about the 
slightest detours. For instance, every so often the right-of-way 
crossed over from one side of the road to the other, and the line 
needed to cross the road within its boundaries. These constant 
road crossings irritated Spivey — Williams was making sharp 
right and left turns. “Steve, you’re costing me a hundred nano- 
seconds,” he’d say. (A nanosecond is one billionth of one sec- 
ond.) And: “Can you at least cross it diagonally ?” 

Spivey was a worrier. He thought that when a person took 
risks, the thing that went wrong was usually a thing the person 
hadn’t thought about, and so he tried to think about the things he 
wouldn’t naturally think about. The Chicago Mercantile Exchange 



might dose and move to New Jersey. The Calumet River might 
prove impassable. Some company with deep pockets — a big Wall 
Street bank, a telecom carrier — might discover what he was 
doing and do it themselves. That last fear — that someone else was 
already out there, digging Ins own straight tunnel — consumed 
him. Every construction person he talked to thought he was out 
of his mind, and yet he was sure the Alleghenies were crawl- 
ing with people who shared his obsession. “When something 
becomes obvious to you,” he said, “you immediately think 
surely someone else is doing this.” 

What never crossed his mind was that, once his line was fin- 
ished, Wall Street would not want to buy the line. Just the reverse: 
He assumed that the line would be the site of a gold rush. Maybe 
for that reason, he and his backers hadn’t thought much about 
how to sell the line until the time came to do it. It was compli- 
cated. What they were selling — speed — was only valuable to the 
extent that it was scarce. What they did not know was the degree 
of scarcity that would maximize the line’s market value. How 
much was it worth to a single player in the U.S. stock market to 
have an advantage in speed over everyone else? How much to 
twenty-five different players — to share the same advantage over 
the rest of the market? To answer these sorts of questions, it helps 
to know how much money traders can make purely from speed 
in the U.S. stock market, and how, exactly, they make it. “No 
one knew this market,” says Spivey. “It was opaque.” 

They considered holding a Dutch auction — that is, start at 
some high reserve price and lower it until the line was bought by 
a single Wall Street firm, which would then enjoy a monopoly. 
They weren’t confident that any one bank or hedge fund would 
fork over the many billions of dollars they assumed the monop- 
oly was worth, and they didn’t like the sound of the inevitable 



headlines in the newspapers: Barksdale Makes Billions Sell- 
ing Out Ordinary American Investor. They hired an industry 
consultant named Larry Tabb, who had caught Jim Barksdale’s 
attention with a paper he’d written called “The Value of a Milli- 
second.” One way to price access to the line, Tabb thought, was 
to figure out how much money might be made from it, from the 
so-called spread trade between New York and Chicago — the 
simple arbitrage between cash and futures. Tabb estimated that 
if a single Wall Street bank were to exploit the countless minus- 
cule discrepancies in price between Thing A in Chicago and 
Thing A in New York, they’d make profits of $20 billion a year. 
He further estimated that there were as many as four hundred 
firms then vying to capture the $20 billion. All of them would 
need to be on the fastest line between the two cities — and there 
were only places for two hundred of them on the line. 

Both estimates happily coincided with Spivey’s sense of the 
market, and he took to saying, with obvious pleasure, “We have 
two hundred shovels for four hundred ditch diggers.” But what 
to charge for each shovel? “It was really a total wet finger in the 
air,” says Brennan Carley, who had worked closely with a lot of 
high-speed traders, and who had been hired by Spivey to sell his 
network to them. “All of us were just guessing.” The number 
they came up with was $300,000 a month, roughly ten times the 
price of the existing telecom lines. The first two hundred stock 
market players willing to pay in advance and sign a five-year 
lease would get a deal: $10.6 million for five years. The traders 
who leased Spread’s line would also need to buy and maintain 
their own signal amplifiers, housed in thirteen amp sites along 
Spread’s route. All-in, the up-front cost to each of the two hun- 
dred traders would come to about $14 million, or a grand total 
of $2.8 billion. 



By early 2010 Spread Networks still hadn’t informed a single 
prospective customer of their existence. A year after the work- 
ers had started digging, the line was, incredibly, still a secret. 
To maximize the line’s shock value and minimize the chance 
that someone else would seek to replicate what they had done, 
or even announce their intention to do so, they decided to wait 
until March 2010, three months before the line was due to be 
completed, before they tried to sell it. How to approach the rich 
and powerful men whose businesses they were about to disrupt? 
“The general modus operandi was to find someone at one of 
these firms one of us knew,” says Brennan Carley. “We’d say, 
‘You know me. You know ofjim Barksdale. We have something 
we want to come over and talk to you about. We can’t tell you 
what it is until we get there. And, by the way, we want you to 
sign an NDA [non-disclosure agreement] before we come in.’ ” 
That’s how they went to Wall Street — in stealth. “There were 
CEOs at every meeting,” says Spivey. The men with whom they 
met were among the most highly paid people in the financial 
markets. The first reaction of most of them was total disbelief. 
“People told me later that they thought, Surely not, but let’s 
talk to him anyway,” says Spivey. Anticipating their skepticism, 
he carried with him a map, four feet by eight feet. He finger- 
walked them through his cross-country tunnel. Even then peo- 
ple still demanded proof. You couldn’t actually see a fiber-optic 
line buried three feet under the ground, but the amp sites were 
highly visible thousand-square-foot concrete bunkers. Light 
fades as it travels; the fainter it becomes, the less capable it is 
of transmitting data. The signals transmitted from Chicago to 
New Jersey needed to be amplified every fifty to seventy-five 
miles, and for the amplifiers that did the work, Spread had built 
these maximum-security bunkers along the route. “I know you 



guys are straight shooters,” one trader said to them. “But I never 
heard of you before. I want to see a picture of this place.” Every 
day for the next three months, Spivey emailed this man a pho- 
tograph of the most recent amp site under construction to show 
him that it was actually being built. 

Once their disbelief faded, most of the Wall Street guys were 
just in awe. Of course they all still asked the usual questions. 
What do I get for my $14 million in assorted fees and expenses? (Two 
glass fibers, one for each direction.) What happens if the line’s cut 
by a backhoe ? (We have people on the line who will have it up 
and running in eight hours.) Where is the backup if your line goes 
doum? (Sorry, there isn’t one.) When can you supply us with the five 
years of audited financial statements that we require before we do busi- 
ness with any firm? (Um, in five years.) But even as they asked 
their questions and ticked their boxes, they failed to disguise 
their wonder. Spivey’s favorite meeting was with a trader who 
sat stone-faced listening to him for fifteen minutes on the other 
side of a long conference table, then leapt to his feet and shouted, 

In these meetings what didn’t get said was often as interest- 
ing as what did. The financial markets were changing in ways 
even professionals did not fully understand. Their new ability 
to move at computer, rather than human, speed had given rise 
to a new class of Wall Street traders, engaged in new kinds of 
trading. People and firms no one had ever heard of were get- 
ting very rich very quickly without having to explain who they 
were or how they were making their money: These people were 
Spread Networks’ target audience. Spivey actually didn’t care 
to pry into their warring trading strategies. “We never wanted 
to come across as if we knew how they were making money on 
this,” he said. He didn’t ask, they didn’t say. But the response of 



many ot them suggested that their entire commercial existence 
depended on being faster than the rest of the stock market — 
and that whatever they were doing wasn’t as simple as the age- 
old cash to futures arbitrage. Some of them, as Brennan Carley 
put it, “would sell their grandmothers for a microsecond.” (A 
microsecond is one millionth of a second.) Exactly why speed 
was so important to them was not clear; what was clear was that 
they felt threatened by this faster new line. “Somebody would 
say, ‘Wait a second,’ ” recalls Carley. “ ‘If we want to continue 
with the strategies we are currently running, we have to be on 
this line. We have no choice but to pay whatever you’re ask- 
ing. And you’re going to go from my office to talk to all of my 
competitors.’ ” 

“I’ll tell you my reaction to them,” says Darren Mulholland, 
a principal at a high-speed trading firm called Hudson River 
Trading. “It was, ‘Get out of my office.’ The thing I couldn’t 
believe was that when they came to my office they were going 
to go live in a month. And they didn’t even know who the cli- 
ents were! They only discovered us from reading a letter we’d 
written to the SEC. . . .Who takes those kinds of business risks?” 

For $300,000 a month plus a few million more in up-front 
expenses, the people on Wall Street then making perhaps more 
money than people have ever made on Wall Street would enjoy 
the right to continue doing what they were already doing. “At 
that point they’d get kind of pissed off,” says Carley. After one 
sales meeting, David Barksdale turned to Spivey and said, Those 
people hate us. Oddly enough, Spivey loved these hostile encoun- 
ters. “It was good to have twelve guys on the other side of the 
table, and they are all mad at you,” he said. “A dozen people told 
us only four guys would buy it, and they all bought it.” (Hudson 
River Trading bought the line.) Brennan Carley said, “We used 



to say, ‘We can’t take Dan to this meeting, because even if they 
have no choice, people do not want to do business with people 
they’re angry with.’ ” 

When the salesmen from Spread Networks moved from the 
smaller, lesser-known Wall Street firms to the big banks, the view 
inside the post-crisis financial world became even more intrigu- 
ing. Citigroup, weirdly, insisted that Spread reroute the line from 
the building next to the Nasdaq in Carteret to their offices in 
lower Manhattan, the twists and turns of which added several 
milliseconds and defeated the line’s entire purpose. The other 
banks all grasped the point of the line but were given pause by 
the contract Spread required them to sign. This contract pro- 
hibited anyone who leased the line from allowing others to use 
it. Any big bank that leased a place on the line could use it for 
its own proprietary trading but was forbidden from sharing it 
with its brokerage customers. To Spread this seemed an obvious 
restriction: The line was more valuable the fewer people that 
had access to it. The whole point of the line was to create inside 
the public markets a private space, accessible only to those will- 
ing to pay the tens of millions of dollars in entry fees. “Credit 
Suisse was outraged,” says a Spread employee who negotiated 
with the big Wall Street banks. “They said, ‘You’re enabling 
people to screw their customers.’ ” The employee tried to argue 
that this was not true — that it was more complicated than that — 
but in the end Credit Suisse refused to sign the contract. Morgan 
Stanley, on the other hand, came back to Spread and said, We 
need you to change the language. “We say, ‘But you’re okay with 
the restrictions?’ And they say, ‘Absolutely, this is totally about 
optics.’ We had to wordsmith it so they had plausible deniabil- 
ity.” Morgan Stanley wanted to be able to trade for itself in a way 
it could not trade for its customers; it just didn’t want to seem as 



if it wanted to. Of all the big Wall Street banks, Goldman Sachs 
was the easiest to deal with. “Goldman had no problem signing 
it,” the Spread employee said. 

It was at just this moment — as the biggest Wall Street banks 
were leaping onto the line — that the line stopped in its tracks. 

There’d been challenges all along the route. After leaving 
Chicago they had tried and failed six times to tunnel 120 feet 
under the Calumet River. They were about to give up and find 
a slower way around when they stumbled upon a century-old 
tunnel that hadn’t been used in forty years. The first amp site 
after leaving Carteret was supposed to be near a mall in Alpha, 
New Jersey. The guy who owned the land said no. “He said he 
knew it was going to be some kind of terrorist target and he 
didn’t want it in the neighborhood,” said Spivey. “There’s always 
little gotchas out there that you have to be careful of.” 

Pennsylvania had proved even more difficult than Spivey had 
imagined. Coming from the east, the line ran to a small forest in 
Sunbury, just off the east bank of the Susquehanna River, where 
it stopped and waited for its western twin. The line coming from 
the west needed to cross the Susquehanna. That stretch of river 
was breathtakingly wide. There was one drill in the world — it 
would cost them $2 million to rent — capable of boring a tunnel 
under the river. In June 2010, the drill was in Brazil. “We need 
a drill that is in Brazil ,” says Spivey. “That idea is quite alarm- 
ing. Obviously someone is using the drill. When do we get to 
use it?” At the last minute they overcame some objections from 
Pennsylvania bridge authorities and were permitted to cross the 
river on the bridge — by boring holes through its concrete pylons 
and running the cable on the underside of the bridge. 

At which point the technical problems gave way to social 
problems. Leaving the bridge, the road split; one branch went 



north; the other, south. If you attempted to travel due east, you 
hit a dead end. The readjust stopped, near a sign beside a levee 
that said, Welcome to Sunbury. Blocking the line’s path were 
two big parking lots. One belonged to a company that manufac- 
tured wire rope, the cable used on ski lifts; the other was owned 
by a century-old grocery store named Weis Markets. To reach 
its twin in the Sunbury forest, the line needed to pass through 
one of these parking lots or travel around the entire city. The 
owners of both Weis Markets and the Wirerope Works were 
hostile or suspicious, or both; they weren’t returning calls. “The 
whole state has been abused by coal companies,” Steve Wil- 
liams explained. “When you say you want to dig, everyone gets 

Going around rather than through the town, Spivey calcu- 
lated, would cost several months and a lot of money and would 
add four microseconds to his route. It would also prevent Spread 
Networks from delivering the cable on time to the Wall Street 
banks and traders ready to write checks for $10.6 million for it. 
But the guy who ran the wire rope factory was for some reason 
so angry with Spread’s local contractor that he wouldn’t speak 
to them. The guy who ran the Weis Markets was even harder 
to reach. His secretary told Spread that he was at a golf tourna- 
ment, and unavailable. He’d already decided — without inform- 
ing Spread Networks — to reject the somewhat strange offer of 
low six figures plus free high-speed Internet access they had 
offered him in exchange for a ten-foot easement under his park- 
ing lot. The line passed too close to his ice cream-making plant. 
The chairman had no interest in signing over a permanent ease- 
ment that would make it difficult to expand the ice cream plant. 

In July 2010 the line dropped back underground beneath the 
bridge in Sunbury and just stopped. “We had all this fiber out 



there and we needed it to talk to each other and it couldn’t,” 
said Spivey. Then, for some reason he never fully understood, 
the wire rope people softened. They sold him the easement he 
needed. The day after Spread Networks acquired lifetime rights 
to a ten-foot-wide path under the wire rope factory’s parking 
lot, it sent out its first press release: “Round-trip travel time from 
Chicago to Newjersey has been cut to 13 milliseconds.” They’d 
set a goal of coming in at under 840 miles and beaten it; the line 
was 827 miles long. “It was the biggest what-the-fuck moment 
the industry had had in some time,” said Spivey. 

Even then, none of the line’s creators knew for sure how 
the line would be used. The biggest question about the line — 
Why ? — remained imperfectly explored. All its creators knew 
was that the Wall Street people who wanted it wanted it very 
badly — and also wanted to find ways for others not to have it. 
In one of his first meetings with a big Wall Street firm, Spivey 
had told the firm’s boss the price of his line: $10.6 million plus 
costs if he paid up front, $20 million or so if he paid in install- 
ments. The boss said he’d like to go away and think about it. He 
returned with a single question: “Can you double the price?” 



U p till the moment of the collapse of the U.S. financial 
system, Brad Katsuyama could tell himself that he bore 
no responsibility for that system. He worked for the 
Royal Bank of Canada, for a start. RBC might be the ninth 
biggest bank in the world, but it was on no one’s mental map of 
Wall Street. It was stable and relatively virtuous, and soon to be 
known for having resisted the temptation to make bad subprime 
loans to Americans or peddle them to ignorant investors. But its 
management didn’t understand just what an afterthought their 
bank was — on the rare occasions American financiers thought 
about them at all. Brad’s bosses had sent him from Toronto to 
New York back in 2002, when he was twenty-four years old, as 
part of a “big push” to become a player on Wall Street. The sad 
truth about the big push was that hardly anyone noticed it. As a 
trader who moved to RBC from Morgan Stanley put it, “When 
I got there, it was like, ‘Holy shit, welcome to the small time!’ ” 
Brad himselt said, “7’he people in Canada are always saying, 



‘We’re paying too much for people in the United States.’ What 
they don’t realize is that the reason you have to pay them too 
much is that no one wants to work for RBC. RBC is a nobody.” 
It was as if the Canadians had summoned the nerve to audition 
for a role in the school play, then turned up for it wearing a car- 
rot costume. 

Before they sent him there to be part of the big push, Brad 
had never laid eyes on Wall Street or New York City. It was his 
first immersive course in the American way of life, and he was 
instantly struck by how different it was from the Canadian ver- 
sion. “Everything was to excess,” he said. “I met more offensive 
people in a year than I had in my entire life. People lived beyond 
their means, and the way they did it was by going into debt. 
That’s what shocked me the most. Debt was a foreign concept in 
Canada. Debt was evil. I’d never been in debt in my life, ever. I 
got here and a real estate broker said, ‘Based on what you make, 
you can afford a $2.5 million apartment.’ I was like, What the 
fuck are you talking about?” In America, even the homeless were 
profligate. Back in Toronto, after a big bank dinner, Brad would 
gather the leftovers into covered tin trays and carry them out to a 
homeless guy he saw every day on his way to work. The guy was 
always appreciative. When the bank moved him to New York, 
he saw more homeless people in a day than he saw back home 
in a year. When no one was watching, he’d pack up the king’s 
banquet of untouched leftovers after the New York lunches and 
walk it down to the people on the streets. “They just looked at 
me like, ‘What the fuck is this guy doing?’ ” he said. “I stopped 
doing it because I didn’t feel like anyone gave a shit.” 

In the United States, Brad also noticed, he was expected to 
accept distinctions between himself and others that he’d simply 
ignored in Canada. Growing up, he’d been one of the very few 



Asian kids in a white suburb of Toronto. During World War II, 
his Japanese Canadian grandparents had been interned in prison 
camps in western Canada. Brad never mentioned this or any- 
thing else having to do with race to his friends, and they ended 
up thinking of him almost as a person who did not have a racial 
identity. His genuine lack of interest in the subject became an 
issue only after he arrived in New York. Worried that it needed 
to do more to promote diversity, RBC invited Brad along with 
a bunch of other nonwhite people to a meeting to discuss the 
issue. Going around the table, people took turns responding to 
a request to “talk about your experience of being a minority at 
RBC.” When Brad’s turn came he said, “To be honest, the only 
time I’ve ever felt like a minority is this exact moment. If you 
really want to encourage diversity you shouldn’t make people 
feel like a minority.” Then he left. The group continued to meet 
without him. 

The episode said as much about him as it did about his new 
home. Ever since he was a little kid, more by instinct than con- 
scious thought, he had resisted the forces that sought to separate 
him from any group to which he felt he belonged. When he 
was seven his mother told him he’d been identified as a gifted 
student, and she offered him the chance to attend special school. 
He told her he wanted to stay with his friends and attend the 
normal school. In high school the track coach thought he could 
be a star (he ran a 4.5-second forty-yard dash), until he told the 
coach that he’d rather play a team sport — he stuck with hockey 
and football. Upon leaving high school at the top of his class, he 
could have gone on scholarship to any university in the world: 
He was not only the best student but a college-caliber tailback 
and a talented pianist. Instead he chose to follow his girlfriend 
and his football teammates to Wilfrid Laurier University, an 



hour or so from Toronto. After he graduated from Laurier, tak- 
ing the prize for best student in the business program, he wound 
up trading stocks at the Royal Bank of Canada — not because he 
had any particular interest in the stock market but because he had 
no idea what else to do for a living. Up till the moment he was 
forced to, he hadn’t really thought about what he wanted to be 
when he grew up, or that he might end up in some radically dif- 
ferent place than the friends he’d grown up with. What he liked 
about the RBC trading floor, aside from the feeling it gave him 
that it would reward his analytical abilities, was that it reminded 
him of a locker room. Another group, to which he naturally 

The RBC trading floor at One Liberty Plaza looked out on 
the holes once filled by the Twin Towers. When Brad arrived, 
the firm was still conducting air quality studies to determine if 
it was safe for its employees to breathe. In time they just sort of 
forgot about what had happened in this place; the hole in the 
ground became the view you looked at without ever seeing it. 

For his first few years on Wall Street, Brad traded U.S. tech 
and energy stocks. He had some fairly abstruse ideas about how 
to create what he called “perfect markets,” and they worked so 
well that he was promoted to run the equity trading depart- 
ment, consisting of twenty or so traders. The RBC trading floor 
had what the staff liked to refer to as a “no-asshole rule”; if 
someone came in the door looking for a job and sounding like 
a typical Wall Street asshole, they wouldn’t hire him, no matter 
how much money he said he could make the firm. There was 
even an expression used to describe the culture: “RBC nice.” 
Although Brad found the expression embarrassingly Canadian, 
he, too, was RBC nice. The best way to manage people, he 
thought, was to convince them that you were good for their 



careers. He further believed that the only way to get people to 
believe that you were good for their careers was actually to be 
good for their careers. These thoughts came naturally to him: 
They just seemed obvious. 

If there was a contradiction between who Brad Katsuyama 
was and what he did for a living, he didn’t see it. He assumed he 
could be a trader on Wall Street without its having the slightest 
effect on his habits, tastes, worldview, or character. And during 
his first few years on Wall Street he appeared to be correct. Just 
by being himself he became, on Wall Street, a great success. 
“His identity at RBC in New York was very simple,” says a 
former colleague. “Brad was the golden child. People thought 
he was going to end up running the bank.” For more or less his 
entire life, Brad Katsuyama had trusted the system; and the sys- 
tem, in return, trusted Brad Katsuyama. That left him especially 
unprepared for what the system was to do to him. 

HIS TROUBLES BEGAN at the end of 2006, after RBC paid $100 
million for a U.S. electronic stock market trading firm called 
Carlin Financial. In what appeared to Brad to be undue haste, 
his bosses back in Canada bought Carlin without knowing much 
about either it or electronic trading. In what he thought to be 
typical Canadian fashion, they had been slow to react to a big 
change in the financial markets; but once they felt compelled to 
act, they’d panicked. “The bank’s run by these Canadian guys 
from Canada,” a former RBC director put it. “They don’t have 
the slightest idea of the ins and outs of Wall Street.” 

In buying Carlin they received a crash course. In a stroke Brad 
found himself working side by side with a group of American 
traders who could not have been less suited to RBC’s culture. 



The first day after the merger, Brad got a call from a worried 
female employee, who whispered, “There is a guy in here with 
suspenders walking around with a baseball bat in his hands, tak- 
ing swings.” That turned out to be Carlin’s founder and CEO, 
Jeremy Frommer, who, whatever else he was, was not RBC 
nice. One of Frommer ’s signature poses was feet up on his desk, 
baseball bat swinging wildly over his head while some poor 
shoeshine guy tried to polish his shoes. Another was to find a 
perch on the trading floor and muse in loud tones about who 
might get fired next. Returning to his alma mater, the Uni- 
versity of Albany, to tell a group of business students the secret 
of his success, Frommer actually said, “It’s not just enough that 
I’m flying in first class. I have to know my friends are flying in 
coach.” “Jeremy was emotional, erratic, and loud — everything 
the Canadians were not,” says one former senior RBC execu- 
tive. “To me, Toronto is like a foreign country,” said Frommer 
later. “The people there are not the same culture as us. They 
take a very cerebral approach to Wall Street. It was just such a 
different world. It was a hard adjustment for me. If you were a 
hitter, you couldn’t swing your dick around the way you could 
in the old days.” 

With each mighty swing Jeremy Frommer scored a direct hit 
on Canadian sensibilities. The first Christmas after the two firms 
merged, he took it upon himself to organize the office party. The 
RBC Christmas party had always been a staid affair. Frommer 
rented out Marquee, the Manhattan nightclub. “RBC doesn’t 
do stuff at Marquee, says one former RBC trader. “Everyone 
was like, ‘What the fuck is going on here?’ ” “I walked in and 
I didn’t know ninety percent of the people there,” says another. 
“It looked like we were in a Vegas hotel lobby bar. There were 
these girls walking around half-naked, selling cigars. I asked, 



‘Who are all these people?’” Into this old-fashioned Canadian 
bank, heretofore immune from the usual Wall Street patholo- 
gies, Frommer imported a bunch of people who were not. “The 
women at Carlin had a different look than the women at RBC,” 
says another former RBC trader delicately. “You got the feeling 
they were hired because they were hot.” With Carlin also came 
a boiler room full of day traders, some of whom had rap sheets 
with various financial police, others of whom were about to 
wind up in jail for financial crimes.” “Carlin was what I always 
imagined a bucket shop was like,” says another former RBC 
trader. “There was a lot of the gold chains attire,” said another. 
It was as if a tribe of 1980s Wall Street alpha males had stum- 
bled upon a time machine and, as a prank, identified the most 
mild-mannered, well-behaved province in Canada and tele- 
ported themselves into it. The RBC guys were at their desks at 
6:30; the Carlin guys rolled in at 8:30 or so, looking distinctly 
unwell. The RBC guys were understated and polite; the Carlin 
guys were brash and loud. “They lied or exaggerated a lot about 
their relationships with accounts,” says a current RBC salesman. 
“They were like, ‘Yeah, I cover [hedge fund giant John] Paulson 
and we’re tight.’ And you’d call Paulson up and they’d barely 
heard of the guy.” 

For reasons Brad did not fully grasp, RBC insisted that he 
move with his entire U.S. stock trading department from their 
offices near the World Trade Center site into Carlin’s building in 
Midtown. This bothered him a lot. Fie got the distinct impres- 
sion that people in Canada had decided that electronic trading 
was the future, even if they didn’t understand why or even what 

* In the room was, among other people, Zvi Goffer, who was later sentenced to ten years 
in jail for orchestrating an insider trading ring in his prior job, with the Galleon Group. 



it meant. Installed in Carlin’s offices, the lkBC people were soon 
gathered to hear a state-of-the-financial-markets address given 
by Frommer. He stood in front of a flat panel computer monitor 
that hung on his wall. “He gets up and says the markets are now 
all about speed,” says Brad. ‘“Trading is all about speed.’ And 
then he says, ‘I’m going to show you how fast our system is.’ He 
had this guy next to him with a computer keyboard. He said 
to him, ‘Enter an order!’ And the guy hit Enter. And the order 
appeared on the screen so everyone could see it. And Frommer 
goes, ‘See! See how fast that was!!!’ ” All the guy had done was 
type the name ol a stock on a keyboard, and the name was dis- 
played on the screen, the way a letter, once it has been typed, 
appears on a computer screen. “Then he goes, ‘Do it again!’ 
And the guy hits the Enter button on the keyboard again. And 
everyone nods. It was five in the afternoon. The market wasn’t 
open; nothing was happening. But he was like, ‘Oh my God, it’s 
happening in real time!’ And I was like, ‘I don’t fucking believe 
this. ’ Brad thought: The guy who just sold us our new electronic trad- 
ing platform either does not know that his display of technical virtuosity 
is absurd, or, worse, he thinks we don’t know. 

As it happened, at almost exactly the moment Jeremy From- 
mer fully entered Brad’s life, the U.S. stock market began to 
behave oddly. Before RBC acquired this supposedly state-of- 
the-art electronic trading firm, his computers worked. Now, 
suddenly, they didn’t. Until he was forced to use some of Carlin’s 
technology, he trusted his trading screens. When his trading 
screens showed 10,000 shares of Intel offered at $22 a share, it 
meant that he could buy 10,000 shares of Intel for $22 a share. 
He had only to push a button. By the spring of 2007, when 
his screens showed 10,000 shares of Intel offered at $22 and he 
pushed the button, the offers vanished. In his seven years as a 



trader he had always been able to look at the screens on his desk 
and see the stock market. Now the market as it appeared on his 
screens was an illusion. 

This was a big problem. Brad’s main role as a trader was to sit 
between investors who wanted to buy and sell big amounts of 
stock and the public markets, where the volumes were smaller. 
Some investor might want to sell a 3-million-share block of 
IBM; the markets would only show demand for 1 million shares; 
Brad would buy the entire block, sell off a million shares of it 
instantly, and then work artfully over the next few hours to 
unload the other 2 million shares. If he didn’t know what the 
markets actually were, he couldn’t price the larger block. He 
had been supplying liquidity to the market; now, whatever was 
happening on his screens was reducing his willingness to do it. 
Unable to judge market risks, he was less happy to take them. 

By June 2007 the problem had grown too big to ignore. An 
electronics company in Singapore called Flextronics announced 
its intention to buy a smaller rival, Solectron, for a bit less than 
$4 a share. A big investor called Brad and said he wanted to sell 
5 million shares of Solectron. The public stock markets — the 
New York Stock Exchange (NYSE) and Nasdaq — showed the 
current market. Say it was 3.70—3.75, which is to say you could 
sell Solectron for $3.70 a share or buy it for $3.75. The problem 
was that, at those prices, only a million shares were bid for and 
offered. The big investor who wished to sell 5 million shares of 
Solectron called Brad because he wanted Brad to take the risk 
on the other 4 million shares. And so Brad bought the shares at 
$3.65, slightly below the price quoted in the public markets. But 
when he turned to the public markets — the markets on his trad- 
ing screens — the share price instantly moved. Almost as if the 
market had read his mind. Instead of selling a million shares at 



$3.70, as he’d assumed he could do, he sold a few hundred thou- 
sand and trigged a minicollapse in the price of Solectron. It was 
as if someone knew what he was trying to do and was reacting 
to his desire to sell before he had fully expressed it. By the time 
he was done selling all 5 million shares, at prices far below $3.70, 
he had lost a small fortune. 

This made no sense to him. He understood how he might 
move the price of an infrequently traded stock simply by sat- 
isfying the demand for the highest bidder. But in the case of 
Solectron, the stock of a company about to be taken over at a 
known price by another company was trading heavily. There 
should be plenty of supply and demand in a very narrow price 
range; it just shouldn’t move very much. The buyers in the mar- 
ket shouldn’t vanish the moment he sought to sell. At that point 
he did what most people do when they don’t understand why 
their computer isn’t working the way it’s supposed to: He called 
tech support. “If your keyboard didn’t work, these were the guys 
who would come up and replace it.” Like tech support every- 
where, their first assumption was that Brad didn’t know what 
he was doing. “‘User error’ was the thing they’d throw at you. 
They just thought of us traders as a bunch of dumb jocks.” He 
explained to them that all he was doing was hitting the Enter 
key on his keyboard: It was hard to screw that up. 

Once it was clear that the problem was more complicated 
than user error, the troubleshooting was bumped to a higher 
level. “They started to send me product people, the people 
who had bought and installed the systems, and they at least sort 
of sounded like technologists.” He explained that the market 
on his screens used to be a fair representation of the actual 
stock market but that now it was not. In return he received 
mainly blank stares. It wound up being me talking to some- 



one and them looking, like, befuddled.” Finally he complained 
so loudly that they sent him the developers, the guys who had 
come to RBC in the Carlin acquisition. “We would hear how 
they had this roomful of Indians and Chinese guys. Rarely 
would you see them on the trading floor. They were called “the 
Golden Goose.” The bank did not want the Golden Goose dis- 
tracted, and, when the geese arrived, they had the air of people 
on leave from some critical mission. They, too, explained to 
Brad that he, and not his machine, was the problem. “They 
told me it was because I was in New York and the markets 
were in New Jersey and my market data was slow. Then they 
said that it was all caused by the fact that there are thousands 
of people trading in the market. They’d say, ‘You aren’t the 
only one trying to do what you’re trying to do. There’s other 
events. There’s news.’ ” 

If that was the case, he asked them, why did the market in 
any given stock dry up only when he was trying to trade in it? 
To make his point, he asked the developers to stand behind 
him and watch while he traded. “I’d say, ‘Watch closely. I 
am about to buy one hundred thousand shares of Amgen. I 
am willing to pay forty-eight dollars a share. There are cur- 
rently one hundred thousand shares of Amgen being offered at 
forty-eight dollars a share — ten thousand on BATS, thirty-five 
thousand on the New York Stock Exchange, thirty thousand 
on Nasdaq, and twenty-five thousand on Direct Edge.’ You 
could see it all on the screens. We’d all sit there and stare at the 
screen and I’d have my finger over the Enter button. I’d count 
out loud to five . . . 

“ ‘One . . . 

“ ‘Two. . . . See, nothing’s happened. 

“ ‘Three. . . . Offers are still there at forty-eight . . . 



“ ‘Four. . . . Still no movement. 

“‘Five.’ Then Fd hit the Enter button and — boom! — all hell 
would break loose. The offerings would all disappear, and the 
stock would pop higher.” 

At which point he turned to the guys standing behind him 
and said, “You see, Fm the event. I am the news.” 

To that the developers had no response. “They were kind of 
like, ‘Ohhh, yeah. Let me look into that.’ Then they’d disap- 
pear and never come back.” Fie called a few times, but “when I 
realized they really had no shot at solving the problem, I just left 
them alone.” 

Brad suspected that the culprit was the technology from Car- 
lin that RBC had more or less bolted onto the side of his trad- 
ing machines. “As the market problem got worse,” he said, “I 
started to just assume my real problem was with how bad their 
technology was.” A pattern was established: The moment he 
attempted to react to the market on his screens, the market 
moved. And it wasn’t just him: The exact same thing was hap- 
pening to all of the RBC stock market traders who worked for 
him. In addition, for reasons he couldn’t fathom, the fees that 
RBC was paying to stock exchanges were suddenly skyrocket- 
ing. At the end of 2007 Brad conducted a study to compare 
what had happened on his trading books to what should have 
happened, or what used to happen, when the stock market as 
stated on his trading screens was the market he experienced. 
“The difference to us was tens of millions of dollars” in losses 
plus fees, he said. “We were hemorrhaging money.” His bosses 
in Toronto called him in and told him to figure out how to 
reduce his rising trading costs. 

Up till then, Brad had taken the stock exchanges for granted. 
When he’d arrived in New York, in 2002, 85 percent of all stock 



market trading happened on the New York Stock Exchange, 
and some human being processed every order. The stocks that 
didn’t trade on the New York Stock Exchange traded on Nas- 
daq. No stocks traded on both exchanges. At the behest of the 
SEC, in turn responding to public protests about cronyism, the 
exchanges themselves, in 2005, went from being utilities owned 
by their members to public corporations run for profit. Once 
competition was introduced, the exchanges multiplied. By early 
2008 there were thirteen different public exchanges, most of 
them in northern New Jersey. Virtually every stock now traded 
on all of these exchanges: You could still buy and sell IBM on 
the New York Stock Exchange, but you could also buy and 
sell it on BATS, Direct Edge, Nasdaq, Nasdaq BX, and so on. 
The idea that a human being needed to stand between investors 
and the market was dead. The “exchange” at Nasdaq or at the 
New York Stock Exchange, or at their new competitors, such 
as BATS and Direct Edge, was a stack of computer servers that 
contained the program called the “matching engine.” There was 
no one inside the exchange to talk to. You submitted an order 
to the exchange by typing it into a computer and sending it into 
the exchange’s matching engine. At the big Wall Street banks, 
the guys who once peddled stocks to big investors had been 
reprogrammed. They now sold algorithms, or encoded trading 
rules designed by the banks, that investors used to submit their 
stock market orders. The departments that created these trading 
algorithms were dubbed “electronic trading.” 

That was why the Royal Bank of Canada had panicked and 
bought Carlin. There was still a role for Brad and traders like 
Brad — to sit between buyers and sellers of giant blocks of stock 
and the market. But the space was shrinking. 

At the same time, the exchanges were changing the way they 



made money. In 2002 they charged every Wall Street broker who 
submitted a stock market order the same simple fixed commis- 
sion per share traded. Replacing people with machines enabled 
the markets to become not just faster but more complicated. The 
exchanges rolled out an incredibly complicated system of fees 
and kickbacks. The system was called the “maker-taker model” 
and, like a lot of Wall Street creations, was understood by almost 
no one. Even professional investors’ eyes glazed over when Brad 
tried to explain it to them. It was the one thing I'd skip, because 
a lot of people just didn’t get it,” he said. Say you wanted to buy 
shares in Apple, and the market in Apple was 400-400.05. If you 
simply went in and bought the shares at $400.05, you were said 
to be “crossing the spread.” The trader who crossed the spread 
was classified as the taker. If you instead rested your order to 
buy Apple at $400, and someone came along and sold the shares 
to you at $400, you were designated a “maker.” In general, the 
exchanges charged takers a few pennies a share, paid makers 
somewhat less, and pocketed the difference — on the dubious 
theory that whoever resisted the urge to cross the spread was 
performing some kind of service. But there were exceptions. 
For instance, the BATS exchange, in Weehawken, New Jersey, 
perversely paid takers and charged makers. 

In early 2008 all of this came as news to Brad Katsuyama. “I 
thought all the exchanges just charged us a flat fee,” he said. “I’m 
like, ‘Holy shit, you mean someone will pay us to trade?’ ” Think- 
ing he was being clever, he had all of RBC’s trading algorithms 
direct the bank s stock market orders to whatever exchange 
would pay them the most for what they wanted to do — which, 
at that moment, happened to be the BATS exchange. “It was a 
total disaster, said Brad. When he tried to buy or sell stock and 
seize the payment from the BATS exchange, the market for that 



stock simply vanished, and the price of the stock moved away 
from him. Instead of being paid, he wound up hemorrhaging 
even more money. 

It was not obvious to Brad why some exchanges paid you to 
be a taker and charged you to be a maker, while others charged 
you to be a taker and paid you to be a maker. No one he asked 
could explain it, either. “It wasn’t like there was anyone saying, 
‘Hey, you should really be paying attention to this.’ Because no 
one was paying attention to this.” To further bewilder the Wall 
Street brokers who sent stock market orders to the exchanges, the 
amounts that were charged varied from exchange to exchange, 
and the exchanges often changed their pricing. To Brad this 
all just seemed bizarre and unnecessarily complicated — and it 
raised all sorts of questions. “Why would you pay anyone to be 
a taker? I mean, who is willing to pay to make a market? Why 
would anyone do that?” 

He took to asking people around the bank who might know 
more than he did. He tried Googling, but there wasn’t really 
anything to Google. One day he was talking to a guy who 
worked on the retail end in Toronto selling stocks to individual 
Canadians. “I said, ‘I’m getting screwed, but I can’t figure out 
who is screwing me.’ And he says, ‘You know, there are more 
players out there in the market now.’ And I say, ‘What do you 
mean more players ?’ He says, ‘You know, there’s this new firm 
that’s now ten percent of the U.S. market.’ ” The guy mentioned 
the firm’s name, but Brad didn’t fully catch it. It sounded like 
Gekko. (The name was Getco.) “I’d never even heard of Getco. 

I didn’t even know the name. I’m like, ‘WHAT??’ They were 
ten percent of the market. How can that be true? It’s insane 
that someone could be ten percent of the U.S. stock market and 
I’m running a Wall Street trading desk and I’ve never heard of 



the place. And why, he wondered, would a guy from retail in 
Canada know about them first? 

He was now running a stock market trading department 
unable to trade properly in the U.S. stock market. He was forced 
to watch people he cared for harassed and upset by a bunch of 
1980s Wall Street throwbacks. And then, in the fall of 2008, as 
he sat and wondered what else might go wrong, the entire U.S. 
financial system went into a freefall. The way Americans han- 
dled their money had led to market chaos, and the market chaos 
created life chaos: The jobs and careers of everyone around him 
were suddenly on the line. “Every day I’d walk home and feel as 
it I had just got hit by a car.” 

He wasn’t naive. He knew that there were good guys and bad 
guys, and that sometimes the bad guys win; but he also believed 
that usually they did not. That view was now challenged. When 
he began to grasp, along with the rest of the world, what big 
American firms had done— rigged credit ratings to make bad 
loans seem like good loans, created subprime bonds designed to 
fail, sold them to their customers and then bet against them, and 
so on his mind hit some kind of wall. For the first time in his 
career, he felt that he could only win if someone else lost, or, 
more likely, that someone else could only win if he lost. He was 
not by nature a zero-sum person, but he had somehow wound 
up in the middle of a zero-sum business. 

His body had always tended to register stress before his mind. 
It was as if his mind refused to accept the possibility of conflict 
even as his body was engaged in that conflict. Now he bounced 
from one illness to another. His sinuses became infected and 
required surgery. His blood pressure, chronically high, skyrock- 
eted. His doctors had him seeing a kidney specialist. 

By early 2009 he’d decided to quit Wall Street. He’d just 



become engaged. After work every day he’d sit down with his 
fiancee, Ashley Hooper — a recent Ole Miss graduate who’d 
grown up in Jacksonville, Florida — to decide where to live. 
They’d whittled the list down to San Diego, Atlanta, Toronto, 
Orlando, and San Francisco. He had no idea what he was going 
to do; he just wanted out. “I thought I could just sell pharmaceu- 
ticals or whatever.” He’d never felt a need to be on Wall Street. 
“It was never a calling,” he said. “1 didn’t think about money 
or the stock market when I was growing up. So the attach- 
ment was not strong.” Maybe more oddly, he hadn’t become 
all that wedded to money, even though RBC was now paying 
him almost $2 million a year. His heart had been in his job, but 
mainly because he really liked the people he worked for and the 
people who worked for him. What he liked about RBC was 
that it had never pressured him to be anyone but himself. The 
bank — or the markets, or perhaps both — was now pushing him 
to be someone else. 

Then the bank, on its own, changed its mind. In February 
2009 RBC parted ways with Jeremy Frommer and asked Brad 
to help find someone to replace him. Even as he had one foot 
out the door, Brad found himself interviewing candidates from 
all over Wall Street — and he saw that basically none of the peo- 
ple who held themselves out as knowledgeable about electronic 
trading understood it. “The problem was that the electronic 
people facing clients were just front men,” he said. “They had 
no clue how the technology worked.” 

He withdrew his foot from the doorway and thought about it. 
Every day, the markets were driven less directly by human beings 
and more directly by machines. The machines were overseen 
by people, of course, but few of them knew how the machines 
worked. He knew that RBC’s machines — not the computers 



themselves, but the instructions to run them — were third-rate, 
but he had assumed it was because the company’s new electronic 
trading unit was bumbling and inept. As he interviewed people 
from the major banks on Wall Street, he came to realize that 
they had more in common with RBC than he had supposed. 
“I’d always been a trader,” he said. “And as a trader you’re kind 
of inside a bubble. You’re just watching your screens all day. 
Now I stepped back and for the first time started to watch other 
traders.” He had a good friend who traded stocks at a big-time 
hedge fund in Greenwich, Connecticut, called SAC Capital. 
SAC Capital was famous (and soon to be infamous) for being 
one step ahead of the U.S. stock market. If anyone was going 
to know something about the market that Brad didn’t know, 
he figured, it would be them. One spring morning he took the 
train up to Greenwich and spent the day watching his friend 
trade. Right away he saw that, even though his friend was using 
technology given to him by Goldman Sachs and Morgan Stan- 
ley and the other big firms, he was experiencing exactly the 
same problem as RBC: The market on his screens was no longer 
the market. His friend would hit a button to buy or sell a stock 
and the market would move away from him. “When I see this 
guy trading and he was getting screwed — I now see that it isn’t 
just me. My frustration is the market’s frustration. And I was 
like, Whoa, this is serious.” 

Brad’s problem wasn’t just Brad’s problem. What people saw 
when they looked at the U.S. stock market — the numbers on the 
screens of the professional traders, the ticker tape running across 
the bottom of the CNBC screen — was an illusion. “That’s when 
I realized the markets are rigged. And I knew it had to do with 
the technology. That the answer lay beneath the surface of the 
technology. I had absolutely no idea where. But that’s when the 



lightbulb went off that the only way I’m going to find out what’s 
going on is if I go beneath the surface.” 

THERE WAS NO way he, Brad Katsuyama, was going to go below 
the surface of the technology. People always assumed, because 
he was an Asian male, that he must be a computer wizard. He 
couldn’t (or wouldn’t) program his own VCR. What he had was 
an ability to distinguish between computer people who didn’t 
actually know what they were talking about and those who did. 
The very best example of the latter, he thought, was Rob Park. 

Park, a fellow Canadian, was a legend at RBC. In college in 
the late 1990s he’d become entranced by what was then a novel 
idea: to teach a machine to behave like a very smart trader. “The 
thing that interested me was taking a trader’s thought process 
and replicating it,” Park said. He and Brad had worked together 
at RBC only briefly, back in 2004, before he left to start his 
own business, but they had hit it off. Rob took an interest in 
the way Brad thought when he traded. Rob then turned those 
thoughts into code. The result was RBC’s most popular trad- 
ing algorithm. Here’s how it worked: Say the trader wanted to 
buy 100,000 shares in General Motors. The algo scanned the 
market; it saw that there were only 100 shares offered. No smart 
trader seeking to buy 100,000 shares would tip his desire for a 
mere 100 shares. The market was too thin. But what was the 
point at which the trader should buy GM stock? The algo- 
rithm Rob built had a trigger point: It only bought stock if the 
amount on offer was greater than the historical average of the 
amount offered. That is, if the market was thick. “The decisions 
he makes make sense,” Brad said of Rob. “He puts an incred- 
ible amount of thought into them. And since he puts so much 



thought into his decisions, he’s capable of explaining those deci- 
sions to others.” 

After Brad persuaded Rob to return to RBC, he had the per- 
fect person to figure out what had happened to the U.S. stock 
market. And in Brad, Rob saw the perfect person to grasp and 
explain to others whatever he discovered. “All Brad needs is a 
translator from computer language to human language,” said 
Park. “Once he has a translator, he completely understands it.” 

Brad wasn’t exactly shocked when RBC finally gave up look- 
ing for someone to run its mess of an electronic trading opera- 
tion and asked him if he would take it over and fix it. Everyone 
else was shocked when he agreed to do it, as (a) he had a safe 
and cushy $2-million-a-year job running the human traders 
and (b) RBC had nothing to add to electronic trading. The mar- 
ket was cluttered; big investors had only so much space on their 
desks for trading algorithms sold by brokers; and Goldman Sachs 
and Morgan Stanley and Credit Suisse had long since overrun 
that space and colonized it. All that was left of RBC’s purchase 
of Carlin was the Golden Goose. Thus Brad’s first question to 
the Golden Goose: How do we plan to make money? They had 
an answer: They planned to open RBC’s first “dark pool.” That, 
as it turned out, was what the Golden Goose had been up to all 
along, writing the software for the dark pool. 

Dark pools were another rogue spawn of the new financial 
marketplace. Private stock exchanges, run by the big brokers, 
they were not required to reveal to the public what happened 
inside them. They reported any trade they executed, but they did 
so with sufficient delay that it was impossible to know exactly 
what was happening in the broader market at the moment the 
trade occurred. Their internal rules were a mystery, and only 
the broker who ran a dark pool knew for sure whose buy and sell 



orders were allowed inside. The amazing idea the big Wall Street 
banks had sold to big investors was that transparency was their 
enemy. If, say, Fidelity wanted to sell a million shares of Microsoft 
Corp. — so the argument ran — they were better off putting them 
into a dark pool run by, say, Credit Suisse than going directly to 
the public exchanges. On the public exchanges, everyone would 
notice a big seller had entered the market, and the market price 
of Microsoft would plunge. Inside a dark pool, no one but the 
broker who ran it had any idea what was happening. 

The cost of RBC’s creating and running its own dark pool, 
Brad now learned, would be nearly $4 million a year. Thus 
his second question for the Golden Goose: How will we make 
more than $4 million from our own dark pool? The Golden 
Goose explained that they’d save all sorts of money in fees 
they paid to the public exchanges — by putting together buy- 
ers and sellers of the same stocks who came to RBC at the 
same time. If RBC had some investor who wanted to buy a 
million shares of Microsoft, and another who wanted to sell 
a million shares of Microsoft, they could simply pair them off 
in the dark pool rather than pay Nasdaq or the New York Stock 
Exchange to do it. In theory this made sense; in practice, not so 
much. “The problem,” said Brad, “was RBC was two percent 
of the market. I asked how often we were likely to have buyers 
and sellers to cross. No one had done the analysis.” The analy- 
sis, once finished, showed that RBC, if it opened a dark pool 
and routed all its clients’ orders into it first, would save about 
$200,000 a year in exchange fees. “So I said, ‘Okay, how else 
will we make money?’ ” 

The answer that came back explained why no one had both- 
ered to do any analysis on dark pools in the first place. There 
was a lot of free money to be made, the computer programmers 



explained, by selling access to the RBC dark pool to outside 
traders. They said there were all these people who will pay to 
be in our dark pool,” recalled Brad. “And I said, ‘Who would 
pay to be in our dark pool? And they said, ‘High-frequency 
traders. Brad tried to think of good reasons why traders of 
any sort would pay RBC for access to RBC’s customers’ stock 
market orders, but he came up with none. “It just felt weird,” 
he said. “I had a feeling of why and the feeling didn’t feel good. 
So I said, ‘Okay, none of this sounds like a good idea. Kill the 
dark pool.’ ” 

That just pissed off a lot of people and fueled suspicions that 
Brad Katsuyama was engaged in some activity other than the 
search for corporate profits. Now he was in charge of a business 
called electronic trading — with nothing to sell. What he had, 
instead, was a fast-growing pile of unanswered questions. Why, 
between the dark pools and the public exchanges, were there 
nearly sixty different places, most of them in New Jersey, where 
you could buy any listed stock? Why did the public exchanges 
fiddle with their own pricing so often — and why did you get paid 
by one exchange to do exactly the same thing for which another 
exchange might charge you? How did a firm he’d never heard 
°f — Getco — trade 10 percent of the entire volume of the stock 
market? How had this guy in the middle of nowhere — in retail in 
Canada — learned of Getco’s existence before him? Why was the 
market displayed on Wall Street trading screens an illusion? 

In May 2009, what appeared to be a scandal involving the 
public stock exchanges added more questions to Brad’s list. 
New York senator Charles Schumer wrote a letter to the 
SEC — then issued a press release telling the world what he had 
done — condemning the stock exchanges for allowing “sophisti- 
cated high-frequency traders to gain access to trading mforma- 



tion before it is sent out widely to other traders. For a fee, the 
exchange will ‘flash’ information about buy and sell orders for 
just a few fractions of a second before the information is made 
publicly available.” That was the first time that Brad had heard 
the term “flash orders.” To the growing list of mental questions, 
he added another: Why would stock exchanges have allowed 
flash trading in the first place? 

HE AND ROB set out to build a team of people to investigate the 
U.S. stock market. “At first 1 was looking for guys who had 
worked in HFT or who had worked at large banks,” said Brad. 
No one who had worked in high-frequency trading would 
return his calls. Finding people who worked for the big banks 
was easier: Wall Street firms were shedding people. Guys who 
wouldn’t have given RBC a second thought were now turning 
up in his office begging for work. “I interviewed more than 
seventy-five people,” he said. “We didn’t hire any of them.” The 
problem with all of these people was that even when they said 
they had worked in electronic trading, they clearly didn’t under- 
stand how the electronics did the trading. 

Instead of waiting for resumes to find him, Brad went looking 
for people who worked in or near the banks’ technology depart- 
ments. In the end his new team consisted of a former Deutsche 
Bank software programmer named Billy Zhao, a former man- 
ager in Bank of America’s electronic trading division named John 
Schwall, and a twenty-two-year-old recent Stanford computer 
science graduate named Dan Aisen. Fie then set out with Rob 
for Princeton, New Jersey, where the Golden Goose resided, to 
figure out if any pieces of the Goose were worth keeping. There 
they found a Chinese programmer named Allen Zhang, who, 



it turned out, had written the computer code for the doomed 
dark pool. “I couldn’t tell who was good and who was not from 
just talking to them, but Rob could,” said Brad. “And it became 
clear that Allen was the Goose.” Or, at any rate, the only part 
of the Goose that might be turned to gold. Allen, Brad noticed, 
had no interest in conforming to the norms of corporate life. He 
preferred to work on his own, in the middle of the night, and 
refused to ever take off his baseball cap, which he wore pulled 
down low over his eyes, giving him the appearance of a getaway 
driver badly in need of sleep. Allen was also incomprehensible: 
What was just possibly English came tumbling out of him so 
quickly and indistinctly that his words tended to freeze the lis- 
tener in his tracks. As Brad put it, “Whenever Allen said any- 
thing, I’d turn to Rob and say, ‘What the fuck did he just say?’ ” 

Once he had a team in place, Brad persuaded his superiors 
at the Royal Bank of Canada to conduct what amounted to a 
series of science experiments in the U.S. stock markets. For the 
next several months he and his team would trade stocks not to 
make money but to test theories — to try to answer his original 
question: Why was there a difference between the stock market 
displayed on his trading screens and the actual market? Why, 
when he went to buy 20,000 shares of IBM offered on his trad- 
ing screens, did the market only sell him 2,000? To search for 
an answer, RBC agreed to let his team lose up to $10,000 a day. 
Brad asked Rob to come up with some theories to spend the 
money on. 

The obvious place to start was the public markets — the thir- 
teen stock exchanges scattered in four different sites run by the 
New York Stock Exchange, Nasdaq, BATS, and Direct Edge. 
Rob invited the exchanges to send representatives to RBC to 
answer a few questions. “We were asking really basic questions: 



‘How does your matching engine work?’ ” recalls Park. “ ‘How 
does it handle a lot of different orders at the same price?’ But 
they sent salespeople and they had no idea. When we kept push- 
ing, they sent product managers, business people who knew a 
little about the technology — but they really didn’t know much. 
They finally sent developers.” They were the guys who actually 
programmed the machines. “The question we wanted to answer 
was, ‘What happens between the time you push the button to 
trade and the time your order gets to the exchange?’ ” says Park. 
“People think pushing a button is as simple as pushing a button. 
It’s not. All these things have to happen. There’s a ton of stuff' 
happening. The data we got from them about what was happen- 
ing at first just seemed random. But we knew the answer was out 
there. It was just a question of how to find it.” 

Rob’s first theory was that the exchanges weren’t simply bun- 
dling all the orders at a given price but arranging them in some 
kind of sequence. You and I might both submit an order to 
buy 1,000 shares of IBM at $30 a share, but you might some- 
how obtain the right to cancel your order if my order is filled. 
“We started getting the idea that people were canceling orders,” 
says Park. “That they were just phantom orders.” Say the mar- 
kets, together, showed 10,000 shares of Apple offered at $400 a 
share. Typically, that didn’t represent one person who wanted 
to sell 10,000 shares of Apple but rather a bunch of smaller sell 
orders lumped together. They suspected that the orders were 
lined up in such a way that some people at the back of the line 
had the ability to jump out of the queue the moment the peo- 
ple in the front of the line sold their shares. “We tried calling 
the exchanges and asking them if that’s what they did,” said 
Park. “But we didn’t even know what words to use.” The fur- 
ther problem was that the trading reports did not separate out 



the exchanges: If you tried to buy 10,000 shares of Apple that 
seemed to be on offer and succeeded in buying only 2,000 of 
them, you weren’t informed which exchanges the 8,000 missing 
shares had vanished from. 

Allen wrote a new program that allowed Brad to send orders 
to a single exchange. Brad was fairly certain that this would 
prove that some, or maybe even all, of the exchanges were 
allowing these phantom orders. But no: When he sent an order 
to a single exchange, he was able to buy everything on offer. 
The market as it appeared on his screens was, once again, the 
market. “I thought, Crap, there goes that theory,” said Brad. 
“And that’s our only theory.” 

It made no sense: Why would the market on the screens be 
real if you sent your order only to one exchange but prove illu- 
sory when you sent your order to all the exchanges at once? 
Lacking an actual theory, Brad’s team began to send orders into 
various combinations of exchanges. First NYSE and Nasdaq. 
Then NYSE and Nasdaq and BATS. Then NYSE, Nasdaq BX, 
Nasdaq, and BATS. And so on. What came back was a further 
mystery. As they increased the number of exchanges, the per- 
centage of the order that was filled decreased; the more places 
they tried to buy stock from, the less stock they actually bought. 
“There was one exception,” said Brad. “No matter how many 
exchanges we sent an order to, we always got one hundred per- 
cent of what was offered on BATS.” Rob Park studied this and 
said, “I had no idea why this would be. I just thought, BATS is 
a great exchange!” 

One morning, while taking a shower, Rob had another the- 
ory. He was picturing a bar chart Allen had created. It showed 
the time it took orders to travel from Brad’s trading desk in the 
World Financial Center to the various exchanges. (To wide- 



spread relief, they’d left Carlin’s old offices and moved back 
downtown.) “I was just visualizing that chart,” he said. “It just 
occurred to me that the bars are different heights. What if they 
were the same height? That got me fired up immediately. I went 
to work and went right to Brad’s office and said, ‘I think it’s 
because we’re not arriving at the same time.’ ” 

The increments of time involved were absurdly small: In 
theory, the shortest travel time, from Brad’s desk to the BATS 
exchange in Weehawken, was about 2 milliseconds, and the 
slowest, from Brad’s desk to Carteret, was around 4 millisec- 
onds. In practice, the times could vary much more than that, 
depending on network traffic, static, and glitches in the pieces 
of equipment between any two points. It took 100 milliseconds 
to blink your eyes; it was hard to believe that a fraction of the 
blink of an eye could have such vast market consequences. Allen 
wrote a program — this one took him a couple of days — that 
built delays into the orders Brad sent to exchanges that were 
faster to get to, so that they arrived at exactly the same time 
as they did at the exchanges that were slower to get to. “It was 
counterintuitive,” says Park. “Because everyone was telling us it 
was all about faster. We had to go faster. And we were slowing 
it down.” One morning they sat down at the screen to test the 
program. Ordinarily, when you hit the button to buy and failed 
to get the stock, the screens lit up red; when you got only some 
of the stock you were after, the screens lit up brown; and when 
you got everything you asked for, the screens lit up green. Allen 
hadn’t taken his Series 7 exam, which meant he wasn’t allowed 
to press the Enter button and make a trade, so Rob actually hit 
the button. Allen watched the screens light up green, and, as 
he later said, “I had the thought: This is too easy.” Rob did not 
agree. “As soon as I pushed the button, I ran to Brad’s desk,” 



recalled Rob. “ ‘It worked! It fucking worked.’ I remember there 
was a pause and then Brad said, ‘Now what do we do?’ ” 

That question implied an understanding: Someone out there 
was using the fact that stock market orders arrived at differ- 
ent times at different exchanges to front-run orders from one 
market to another. Knowing that, what do you do next? That 
question suggested another: Do you use this knowledge to join 
whatever game is being played in the stock market? Or for some 
other purpose? It took Brad roughly six seconds to answer the 
question. “Brad said, ‘We have to go on an educational cam- 
paign,’ ” recalls Park. “It would have been very easy to make 
money off this. He just chose not to.” 

THEY NOW HAD an answer to one of their questions — which, as 
always, raised another question. “It’s 2009,” said Brad. “This had 
been happening to me for almost three years. There’s no way 
I’m the first guy to have figured this out. So what happened to 
everyone else?” They also had a tool they could sell to investors: 
the program Allen had written to build delays into the stock 
exchange orders. Before they did that, they wanted to test it on 
RBC’s own traders. “I remember being at my desk,” said Park, 
“and you hear people going, ‘OOOOOOO!’ and ‘Holy shit, 
you can buy stock!’ ” The tool enabled the traders to do the job 
they were meant to do: take risk on behalf of the big investors 
who wanted to trade big chunks of stock. They could once again 
trust the market on their screens. The tool needed a name. Brad 
and his team stewed over this until one day a trader stood up at 
his desk and hollered, “Dude, you should just call it Thor! The 
hammer!” Someone was assigned to figure out what Thor might 
be an acronym for, and they found some words that worked, but 



no one remembered them. The tool was always just Thor. “I 
knew we were onto something when Thor became a verb,” said 
Brad. “When I heard guys shouting, ‘Thor it!’” 

The other way he knew they were on to something was from 
conversations he had with a few of the world’s biggest money 
managers. The first visit Brad and Rob Park made was to Mike 
Gitlin, who oversaw $700 billion in U.S. stock market invest- 
ments for T. Rowe Price. The story they told didn’t come to 
Gitlin as a complete shock. “You could see that something had 
just changed,” said Gitlin. “You could see that when you were 
trading a stock, the market knew what you were going to do, 
and it was going to move against you.” But what Brad described 
was a far more detailed picture of the market than Gitlin had ever 
considered — and, in that market, all the incentives were screwed 
up. The Wall Street brokerage firm deciding where to send 
T. Rowe Price’s buy and sell orders had a great deal of power 
over how and where those orders got submitted. The firms were 
now paid for sending orders to some exchanges and billed for 
sending orders to others. Did the broker resist these incentives 
when they didn’t align with the interests of the investors he was 
meant to represent? No one could say. Another wacky incentive 
was called “payment for order flow.” As of 2010, every Ameri- 
can stockbroker and all the online brokers effectively auctioned 
their customers’ stock market orders. The online broker TD 
Ameritrade, for example, was paid hundreds of millions of dol- 
lars each year to send their orders to a high-frequency trading 
firm called Citadel, which executed the orders on their behalf. 
Why was Citadel willing to pay so much to see the flow? No 
one could say with certainty. 

It had been hard to measure the cost of the new market struc- 
ture. But now there was a tool for gauging not just how orders 



reached their destination but also how much money this new 
Wall Street intermediation machine was removing from the 
pockets of investors large and small: Thor. Brad explained to 
Mike Gitlin how his team had placed big trades to measure how 
much more cheaply they bought stock when they removed the 
ability of the machine to front-run them. For instance, they 
bought 10 million shares of Citigroup, then trading at roughly 
$4 per share, and saved $29,000 — or less than a tenth of 1 per- 
cent of the total price. “That was the tax,” said Rob Park. It 
sounded small until you realized that the average daily volume 
in the U.S. stock market was $225 billion. The same tax rate 
applied to that sum came to more than $160 million a day. “It 
was so insidious because you couldn’t see it,” said Brad. “It hap- 
pens on such a granular level that even if you tried to line it up 
and figure it out you wouldn’t be able to do it. People are getting 
screwed because they can’t imagine a microsecond.” 

Thor showed you what happened when a Wall Street firm 
helped an investor to avoid paying the tax. The evidence was 
indirect but, to Gitlin’s mind, damning. The mere existence 
of Brad Katsuyama was totally shocking. “To have RBC have 
the foremost electronic trading expert in the world was a little 
strange,” said Gitlin. “You would not think that is where the 
world’s foremost electronic expert would reside.” 

The discovery of Thor was not the end of a story; it was 
closer to a beginning. Brad and his team were building a mental 
picture of the financial markets after the crisis. The market was 
now a pure abstraction. It called to mind no obvious picture 
to replace the old one that people still carried around in their 
heads. The same old ticker tape ran across the bottom of televi- 
sion screens — even though it represented only a tiny fraction of 
the actual trading. Market experts still reported from the floor 



of the New York Stock Exchange, even though trading no lon- 
ger happened there. For a market expert truly to get inside 
the New York Stock Exchange, he’d need to climb inside a 
tall black stack of computer servers locked inside a cage locked 
inside a fortress guarded by a small army of heavily armed men 
and touchy German shepherds in Mahwah, New Jersey. If he 
wanted an overview of the entire stock market — or even the 
trading in a single company like IBM — he’d need to inspect 
the computer printouts from twelve other public exchanges 
scattered across northern New Jersey, plus records of the private 
dealings that occurred inside the growing number of dark pools. 
If he tried to do this, he’d soon learn that there actually was no 
computer printout. At least no reliable one. No mental picture 
existed of the new financial market. There was only this yellow- 
ing photograph of a market now dead that served as a stand-in 
for the living. 

Brad had no idea how dark and difficult the picture he’d create 
would become. All he knew for sure was that the stock market 
was no longer a market. It was a collection of small markets scat- 
tered across New Jersey and lower Manhattan. When bids and 
offers for shares sent to these places arrived at precisely the same 
moment, the markets acted as markets should. If they arrived 
even a millisecond apart, the market vanished, and all bets were 
off. Brad knew that he was being front-run — that some other 
trader was, in effect, noticing his demand for stock on one 
exchange and buying it on others in anticipation of selling it to 
him at a higher price. Ele’d identified a suspect: high-frequency 
traders. “I had a sense that the problems are being caused by this 
new participant in the market,” said Brad. “I just didn’t know 
how they were doing it.” 

By late 2009 U.S. high-frequency trading firms were flying 



to Toronto with offers to pay Canadian banks to expose their 
customers to high-frequency traders. Earlier that year, one of 
RBC’s competitors, the Canadian Imperial Bank of Commerce 
(CIBC), had sublet its license on the Toronto Stock Exchange to 
several high-frequency trading firms and, within a few months, 
had seen its historically stable 6-7 percent share of Canadian 
stock market trading triple.* Senior managers at the Royal Bank 
of Canada were now arguing that the bank should create a Cana- 
dian dark pool, route their Canadian customers’ stock market 
orders into it, and then sell to high-frequency traders the right 
to operate inside the dark pool. Brad thought that it made a lot 
more sense for RBC simply to expose the new game for what it 
was, and perhaps establish themselves as the only broker on Wall 
Street not conspiring to screw investors. “The only card left to 
play was honesty,” as Rob Park put it. 

Brad argued to his bosses that he should be permitted to 
launch what amounted to a public information campaign. He 
wanted to go out and explain, to anyone with money to invest 
in the United States stock markets, that they were now the prey. 
He wanted to tell them about this new weapon they might use 
to defend themselves from the predator. But the market was 

* The rules of the Canadian stock market are different from the rules of the U.S. stock 
market. One rule in Canada that does not exist in the United States is “broker priority.” 
The idea is to enable brokerage firms that have both sides of a trade to pair off buyers and 
sellers without the interference of other buyers and sellers. For example, imagine that 
CIBC (representing some investor) has a standing order to buy shares in Company X at 
$20 a share, but that it is not alone, and several other banks also have standing orders for 
Company X’s shares at $20. If CIBC then enters the market with an order from another 
CIBC customer to sell shares in Company X at $20, the CIBC buyer has priority on 
the trade and is the first to have his order filled. By allowing high-frequency traders to 
operate with CIBC’s license, CIBC was, in effect, creating lots of collisions between its 
own customers and the HFT firms. 



already pressuring him to say nothing at all. He was in a race 
to win a debate in front of RBC’s top management about how 
to respond to the newly automated stock markets. All he had 
going for him was his weird discovery, which proved . . . what, 
exactly? That the stock market now behaved strangely, except 
when it didn’t? The RBC executives who wanted to join forces 
with high-frequency traders knew as little about high-frequency 
trading as he did. “I needed someone from the industry to verify 
that what I was saying was real,” said Brad. He needed, specifi- 
cally, someone from deep inside the world of high-frequency 
trading. He’d spent the better part of a year cold-calling strang- 
ers in search of an HFT strategist willing to defect. He now sus- 
pected that every human being who knew how high-frequency 
traders made money was making too much money doing it to 
stop and explain what was going on. He needed to find another 
way in. 



P art of Ronan’s problem was that he didn’t look like a Wall 
Street trader. He had pale skin and narrow, stooped shoul- 
ders, and the uneasy caution of a man who has survived 
one potato famine and is expecting another. He also lacked the 
Wall Street trader’s ability to bury his self-doubt, and to seem 
more important and knowledgeable than he actually was. He 
was wiry and wary, like a mongoose. And yet from the moment 
he caught his first glimpse of a Wall Street trading floor, in his 
early twenties, Ronan Ryan badly wanted to work on Wall 
Street — and couldn’t understand why he didn’t belong. “It’s hard 
not to get enamored of being one of these Wall Street guys who 
people are scared of and make all this money,” he said. But it was 
hard to imagine anyone being scared of Ronan. 

The other part of Ronan’s problem was his inability or 
unwillingness to disguise his modest origins. Born and raised in 
Dublin, he’d moved to America in 1990, when he was sixteen. 
The Irish government had sent his father to New York to talk 



American companies into moving to Ireland for the tax benefits, 
but few imagined that they would do so. Ireland was poor and 
dreary (“kind of like a shithole, to be honest”). His father, who 
was not made of money, had spent every last penny he had to 
rent a house in Greenwich, Connecticut, so that Ronan might 
attend the Greenwich public high school and see what life was 
like on the “right side of the tracks.” “I couldn’t believe it,” says 
Ronan. “The kids had their own cars at sixteen! Kids would 
complain they had to ride on a school bus. I’d say, ‘This fucking 
thing actually takes you to school! And it’s free! I used to walk 
three miles.’ It’s hard not to love America.” When Ronan was 
twenty-two, his father was recalled to Ireland; Ronan stayed 
behind. He didn’t think of Ireland as a place anyone would 
ever go back to if given the choice, and he’d now embraced his 
idea of the American Dream — Greenwich, Connecticut, ver- 
sion. The year before, through an Irish guy his father had met, 
he’d landed a summer internship in the back office at Chemical 
Bank and had been promised a place in the management train- 
ing program. 

Then they canceled the training program; the Irish guy van- 
ished. Graduating from Fairfield University in 1996, he sent let- 
ters to all the Wall Street banks but received just one false flicker 
of interest, from what, even to his untrained eyes, was a vaguely 
criminal, pump-and-dump penny stock brokerage firm. “It’s 
not as easy as you think to get a job on Wall Street,” he said. “I 
didn’t know anyone. My family had no contacts whatsoever. We 
knew no one.” 

Eventually he gave up trying. He met another Irish guy who 
happened to work in the New York office of MCI Communi- 
cations, the big telecom company. “He gave me a job strictly 
because I was Irish,” said Ronan. “I guess he had a few charity 



cases a year. I was one of them.” For no particular reason other 
than that no one else would hire him, he went to work in the 
telecom industry. 

The first big job they gave him was to make sure that the 
eight thousand new pagers MCI had sold to a big Wall Street 
firm were well received. As he was told, “People are really sensi- 
tive about their pagers.” Ronan traveled in the back of a repair 
truck in the summer heat to some office building to deliver the 
new pagers. He set up his little table at the back of the truck and 
unpacked the crates and waited for the Wall Street people to 
come and get their new pagers. An hour into it he was sweat- 
ing and huffing inside the truck while a line of people waited 
for their pagers, and a crowd had formed, of guys to whom he’d 
already given the pagers: pager protestors. “These new pagers 
suckl ” and “I hate this fucking pager!” they screamed, as he tried 
to pass out even more pagers. As he dealt with the revolt, one 
of the Wall Street firms’ secretaries called him about her boss’s 
new pager. She was so despondent about the thing that Ronan 
thought he could hear her crying. “She keeps saying over and 
over, ‘It’s too big! It’s going to really hurt him! It’s too big! It’s 
going to really hurt him!’ ” Ronan was now totally confused: 
How could a pager inflict harm on a grown man? It was a tiny 
box, an inch by an inch and a half. “Then she tells me he’s a 
midget, and it would dig into his side when he bent over,” said 
Ronan. “And that he wasn’t like a normal-sized midget. He was 
a really small dude. And I’m thinking, but I don’t say it because I 
don’t want her to think I’m a dick, Why don’t you just strap it onto 
his back, like a backpack?” 

At that moment, and others like it, many things crossed 
Ronan s mind that he did not say. Sizing pagers to little Wall 
Street people, and being hollered at by big Wall Street people 



who didn’t like their new gadgets, was not what he’d imagined 
doing with his life. He was upset he hadn’t found a path onto 
Wall Street. He decided to make the best of it. 

That turned out to be the view that MCI offered him of the 
entire U.S. telecom system. Ronan had always been handy, but 
he’d never actually studied anything practical. He knew next to 
nothing about technology. Now he started to learn all about it. 
“It’s pretty captivating, when you take the nerdiness out of it, 
how this shit works,” he said. How a copper circuit conveyed 
information, compared to a glass fiber. How a switch made by 
Cisco compared to a switch made by Juniper. Which hardware 
companies made the fastest computer equipment, and which 
buildings in which cities contained floors that could withstand 
the weight of that equipment — old manufacturing buildings 
were best. He also learned how information actually traveled 
from one place to another — which was usually not in a straight 
line run by a single telecom carrier but in a convoluted path run 
by several. “When you make a call to New York from Florida, 
you have no idea how many pieces of equipment you have to 
go through for that call to happen. You probably just think it’s 
fucking like two cans and a piece of string. But it’s not.” A cir- 
cuit that connected New York City to Florida would have Veri- 
zon on the New York end, BellSouth on the Florida end, and 
MCI in the middle; it would zigzag from population center to 
population center; once it got there it would wind in all sorts 
of crazy ways through skyscrapers and city streets. To sound 
knowing, telecom people liked to say that the fiber routes ran 
through “the NFL cities.” 

That was another thing Ronan learned: A lot of people in 
and around the telecom industry were more knowing than 
knowledgeable. The people at MCI who sold the technology 



often didn’t actually understand it and yet were paid far better 
than people, like him, who simply fixed problems. Or, as he put 
it, “I’m making thirty-five and they’re making a buck twenty 
and they’re fucking idiots.” He got himself moved to sales and 
became a leading salesperson. A few years into the job, he was 
lured from MCI by Qwest Communications; three years later, 
he was lured from Qwest by another big telecom carrier, Level 3. 
He was now making good money — a couple of hundred grand a 
year. By 2005, he also couldn’t help but notice, his clients were 
more likely than ever to be big Wall Street banks. He spent 
entire weeks inside Goldman Sachs and Lehman Brothers and 
Deutsche Bank, figuring out the best routes to run fiber and the 
best machines to hook that fiber up to. He hadn’t lost his origi- 
nal ambition. At some point on every Wall Street job he had, 
he’d nose around for a job opening. “I’m thinking: I’m meeting 
so many people. Why can’t I get a job at one of these places?” 
Actually, the big banks offered him jobs all the time, but the jobs 
were never finance jobs. They offered him tech jobs — working 
in some remote site with computer hardware and fiber-optic 
cable. There was a vividly clear class distinction between tech 
guys and finance guys. The finance guys saw the tech guys as 
faceless help and were unable to think of them as anything else. 
“They always said the same thing to me: ‘You’re a boxes and 
lines guy,’ ” he said. 

Then, in 2006, BT Radianz called. Radianz was born of 
9/11, after the attacks on the World Trade Center knocked out 
big pieces of Wall Street’s communication system. The company 
promised to build for big Wall Street banks a system less vulner- 
able to outside attack than the existing system. Ronan’s job was 
to sell the financial world on the idea of subcontracting their 
information networks to Radianz. In particular, he was meant 



to sell the banks on “co-locating” their computers in Radianz’s 
data center in Nutley, New Jersey. But not long after he started 
his job at Radianz, Ronan had a different sort of inquiry, from 
a hedge fund based in Kansas City. The caller said he worked 
at a stock market trading firm called Bountiful Trust, and that 
he had heard Ronan was expert at moving financial data from 
one place to another. Bountiful Trust had a problem: In making 
trades between Kansas City and New York, it took them too 
long to determine what happened to their orders — that is, what 
stocks they had bought and sold. They also noticed that, increas- 
ingly, when they placed their orders, the market was vanishing 
on them, just as it was vanishing on Brad Katsuyama. “He says, 
‘My latency time is forty-three milliseconds,’ ” recalls Ronan. 
“And I said, ‘What the hell is a millisecond?’ ” 

Latency was simply the time between the moment a signal 
was sent and when it was received. There were several factors 
that determined the latency of a stock market trading system: the 
boxes, the logic, and the lines. The boxes were the machinery 
the signals passed through on their way from Point A to Point 
B: the computer servers and signal amplifiers and switches. The 
logic was the software, the code instructions that operated the 
boxes. Ronan didn’t know much about software, except that, 
more and more, it seemed to be written by Russian guys who 
barely spoke English. The lines were the glass fiber-optic cables 
that carried the information from one box to another. The sin- 
gle biggest determinant of speed was the length of the fiber, or 
the distance the signal needed to travel to get from Point A to 
Point B. Ronan didn’t know what a millisecond was, but he 
understood the problem with this Kansas City hedge fund: It 
was in Kansas City. Light in a vacuum traveled at 186,000 miles 
per second, or, put another way, 186 miles a millisecond. Light 



inside of fiber bounced oft' the walls and so traveled at only about 
two-thirds of its theoretical speed. But it was still fast. The big- 
gest enemy of the speed of a signal was the distance the signal 
needed to travel. “Physics is physics — this is what the traders 
didn’t understand,” said Ronan. 

The whole reason Bountiful Trust had set up shop in Kansas 
City was that its founders believed that it no longer mattered 
where they were physically located. That Wall Street was no 
longer a place. They were wrong. Wall Street was, once again, a 
place. It wasn’t actually on Wall Street now. It was in New Jer- 
sey. Ronan moved the computers from Kansas City to Radianz’s 
data center in Nutley and reduced the time it took them to find 
out what they had bought and sold from 43 milliseconds to 3.8 

From that moment the demand on Wall Street for Ronan’s 
services intensified. Not just from banks and well-known high- 
frequency trading firms but also from prop shops (proprietary 
trading firms) no one had ever heard of, with just a few guys in 
them. All wanted to be able to trade faster than the others. To 
be faster they needed to find shorter routes for their signals to 
travel; to be faster they needed the newest hardware, stripped 
down to its essentials; to be faster they also needed to reduce the 
physical distance between their computers and the computers 
inside the various stock exchanges. Ronan knew how to solve 
all of these problems. But as all his new customers housed their 
computers inside the Radianz data center in Nutley, this was a 
tricky business. Ronan says, “One day a trader calls and asks, 
Where am I in the room?’ I’m thinking, In the room? What do 
you mean ‘in the room’? What the guy meant, it turned out, was in 
the room." He was willing to pay to move his computer that sent 
orders into the stock market as close as possible to the pipe that 



exited the building in Nutley — so that he would have a slight 
jump on the other computers in the room. Another trader then 
called Ronan to say that he had noticed that his fiber-optic cable 
was a few yards longer than it needed to be. Instead of having 
it wind around the outside of the room with everyone else’s 
cable — which helped to reduce the heat in the room — the trader 
wanted his cable to hew a straight line right across the middle 
of the room. 

It was only a matter of time before the stock exchanges figured 
out that, if people were willing to spend hundreds of thousands 
of dollars to move their machines around inside some remote 
data center just so they might be a tiny bit closer to the stock 
exchange, they’d pay millions to be inside the stock exchange 
itself. Ronan followed them there. He came up with an idea: 
sell proximity to Wall Street as a service. Call it “proximity ser- 
vices.” “We tried to trademark proximity, but you can’t because 
it’s a word,” he said. What he wanted to call proximity soon 
became known as “co-location,” and Ronan became the world’s 
authority on the subject. When they ran out of ways to reduce 
the length of their cable, they began to focus on the devices on 
either end of the cable. Data switches, for instance. The differ- 
ence between fast data switches and slow ones was measured in 
microseconds (millionths of a second), but microseconds were 
now critical. “One guy says to me, ‘It doesn’t matter if I’m one 
second slower or one microsecond; either way I come in sec- 
ond place.’” The switching times fell from 150 microseconds 
to 1.2 microseconds per trade. “And then,” says Ronan, “they 
started to ask, ‘What kind of glass are you using?’ ” All opti- 
cal fibers were not created equal; some kinds of glass conveyed 
light signals more efficiently than others. And Ronan thought: 
Never before in human history have people gone to so much 



trouble and spent so much money to gain so little speed. “People 
were measuring the length of their cables to the foot inside the 
exchanges. People were buying these servers and chucking them 
out six months later. For microseconds.” 

He didn’t know how much money high-frequency traders 
were making, but he could guess from how much they were 
spending. From the end of 2005 to the end of 2008, Radi- 
anz alone billed them nearly $80 million — -just for setting up 
their computers near the stock exchange matching engines. And 
Radianz was hardly the only one billing them. Seeing that the 
fiber routes between the New Jersey exchanges were often less 
than ideal, Ronan prodded a company called Hudson Fiber into 
finding straighter ones. Hudson Fiber was now doing a land- 
office business digging trenches in places that would give Tony 
Soprano pause. Ronan could also guess how much money high- 
frequency traders were making by the trouble they took to con- 
ceal how they made it. One HFT firm he set up inside one of the 
stock exchanges insisted that he wrap their new computer serv- 
ers in wire gauze — to prevent anyone from seeing their blink- 
ing lights or improvements in their hardware. Another HFT 
firm secured the computer cage nearest the exchange’s matching 
engine — the computer code that, in effect, was now the stock 
market. Formerly owned by Toys “R” Us (the computers prob- 
ably ran the toy store’s website), the cage was emblazoned with 
store logos. The HFT firm insisted on leaving the Toys “R” Us 
logos in place so that no one would know they had improved 
their position, in relation to the matching engine, by several 
feet. “They were all paranoid,” said Ronan. “But they were 
right to be. If you know how to pickpocket someone and you 
were the pickpocketer, you would do the same thing. You’d see 
someone find a new switch that was three microseconds faster, 



and in two weeks everyone in the data center would have the 
same switch.” 

By the end of 2007 Ronan was making hundreds of thousands 
of dollars a year building systems to make stock market trades 
faster. He was struck, over and over again, by how little the 
traders he helped understood of the technology they were using. 
“They’d say, ‘Aha! I saw it — -it’s so fast!’ And I’d say, ‘Look, I’m 
happy you like our product. But there’s no fucking way you saw 
anything.’ And they’re like, ‘I saw it!’ And I’m like, ‘It’s three 
milliseconds — it’s fifty times faster than the blink of an eye.’ ” 
He was also keenly aware that he had only the faintest idea of 
the reason for this incredible new lust for speed. He heard a 
lot of loose talk about “arbitrage,” but what, exactly, was being 
arbitraged, and why did it need to be done so fast? “I felt like the 
getaway driver,” he said. “Each time, it was like, ‘Drive faster! 
Drive faster!’ Then it was like, ‘Get rid of the airbags!’ Then it 
was, ‘Get rid of the fucking seats!’ Towards the end I’m like, 
‘Excuse me, sirs, but what are you doing in the bank?’ ” He had 
a sense of the technological aptitude of the various players. The 
two biggest high-frequency trading firms, Citadel and Getco, 
were easily the smartest. Some of the prop shops were smart, 
too. The big banks, at least for now, were all slow. 

Beyond that, he didn’t even really know much about his cli- 
ents. The big banks — Goldman Sachs, Credit Suisse — everyone 
had heard of. Others — Citadel, Getco — were famous on a small 
scale. He learned that some of these firms were hedge funds, 
which meant that they took money from outside investors. But 
most of them were prop shops, trading only their own found- 
ers’ money. A huge number of the firms he dealt with — Hudson 
River Trading, Eagle Seven, Simplex Investments, Evolution 
Financial Technologies, Cooperfund, DRW — no one had ever 



heard of, and the firms obviously intended to keep it that way. 
The prop shops were especially strange, because they were 
both transient and prosperous. “They’d be just five guys in a 
room. All of them geeks. The leader of each five-man pack is 
just an arrogant version of that geek. A fucking arrogant ver- 
sion of that.” One day a prop shop was trading; the next, it had 
closed, and all the people in it had moved to work for some big 
Wall Street bank. One group of guys Ronan saw over and over: 
four Russian, one Chinese. The arrogant Russian guy who was 
clearly their leader was named Vladimir. Vladimir and his boys 
ping-ponged from prop shop to big bank and back to prop shop, 
writing the computer code that made the actual stock market 
trading decisions. Ronan watched them meet with one of the 
most senior guys at a big Wall Street bank that hoped to employ 
them — and the Wall Street big shot sucked up to them. “He 
walks into the meeting and says, ‘I’m always the most important 
man in the room, but in this case Vladimir is.’ ’ Ronan knew 
that these roving bands of geeks felt nothing but condescen- 
sion toward the less technical guys who ran the big Wall Street 
firms. I was listening to them talk about some calculation they 
had been asked to make, and Vladimir goes, ‘Ho, ho, ho. That’s 
what Americans call math.’ He said it like moth. That’s what 
Americans call moth. I thought, I’m fucking Irish, but fuck you 
guys. This country gave you a shot.” 

By early 2008 Ronan was spending a lot of his time abroad, 
helping high-frequency traders exploit the Americanization of 
foreign stock markets. A pattern emerged: A country in which 
the stock market had always traded on a single exchange — 
Canada, Australia, the UK — would, in the name of free-market 
competition, permit the creation of a new exchange. The new 
exchange was always located at some surprising distance from the 



original exchange. In Toronto it was inside an old department 
store building across the city from the Toronto Stock Exchange. 
In Australia it was mysteriously located not in the Sydney finan- 
cial district but across Sydney Harbor, in the middle of a resi- 
dential district. The old London Stock Exchange was in central 
London. BATS created a British rival in the Docklands, NYSE 
created another, outside of London, in Basildon, and Chi-X cre- 
ated a third in Slough. Each new exchange gave rise to the need 
for high-speed routes between the exchanges. “It was almost 
like they picked places to set up exchanges so that the market 
would fragment,” said Ronan. 

He still didn’t have a job on Wall Street, but Ronan had every 
reason to be pleased with himself and with his career. In 2007, 
the first year of the speed boom, he’d made $486,000, nearly 
twice as much as he’d ever made. Yet he did not feel pleased 
with himself or with his career. He was obviously good at what 
he did, but he had no idea why he was doing it, and he wanted 
to. At the end of 2007, on New Year’s Eve, he found himself 
sitting in a pub in Liverpool with “Let It Be” playing dully on 
the radio. His wife had given him the trip as this lovely gift. 
Around a miniature soccer ball she’d wrapped a note that said 
she’d bought him a plane ticket to England and a ticket to see his 
favorite football team. “I’m doing something I always dreamed 
about doing, and it was about the most depressing moment I’ve 
ever had in my life,” said Ronan. “I’m thirty-four years old. I’m 
thinking it’s never going to get any better. I’m going to be fuck- 
ing Willy Loman for the rest of my life.” He felt ordinary. 

In the fall of 2009, out of the blue, the Royal Bank of Canada 
called him and invited him to interview for a job. He was more 
than a little wary. He’d barely heard of RBC, and when he 
checked out their website it told him next to nothing. He’d 



grown weary of self-important Wall Street traders who wanted 
him to do their manual labor for them. “I said, ‘I mean no 
disrespect, but if you’re calling to offer me some tech job, I 
have no fucking interest.’ ” The RBC guy who called him — 
Brad Katsuyama — insisted that it wasn’t a tech job but a job in 
finance, on a trading floor. 

Ronan met Brad at seven the next morning and wondered if 
that was a Wall Street thing, hauling people in for interviews at 
seven in the morning. Brad asked him a bunch of questions and 
then invited him back to meet his bosses. In what seemed to 
Ronan like “the quickest hiring in the history of Wall Street,” 
RBC offered him a job on the trading floor. It paid $125,000, 
or roughly a third of what Ronan was making peddling speed 
to high-frequency traders. It came with a fancy title: Head of 
High-Frequency Trading Strategies. For a chance to work on a 
Wall Street trading floor, Ronan was willing to take a big pay 
cut. “To be honest, I would have taken less,” he said. But the 
title disturbed him, because, as he put it, “I didn’t know any 
high-frequency trading strategies.” He was so excited to have 
finally landed a job on a Wall Street trading floor that he didn’t 
bother to ask the obvious question. His wife asked it for him. 
“She says to me, ‘What are you going to do for them?’ And I 
realized I didn’t really fucking know. I really, honest to God, 
have no idea what the job is. There was no job description ever 
discussed. He never told me what he wanted me for.” 

IN THE FALL of 2009, an article in a trade magazine caught Brad 
Katsuyama’s eye. He’d spent the better part of a year trying and 
failing to find anyone who actually worked in what was now 
regularly referred to as high-frequency trading who was willing 



to explain to him how he made his money. The article claimed 
that HFT technologists were unhappy with the widening gulf 
in pay between themselves and the senior trading strategists of 
their firms, some of whom were rumored to be taking home 
hundreds of millions of dollars a year. He went looking for one 
of these unhappy technologists. The very first call he made, to a 
guy at Deutsche Bank who dealt often with HFT, gave him two 
names. Ronan’s was the first. 

In his interview, Ronan described to Brad what he’d wit- 
nessed inside the exchanges: the frantic competition for nano- 
seconds, the Toys “R” Us cage, the wire gauze, the war for space 
within the exchanges, the tens of millions being spent by high- 
frequency traders for tiny increments of speed. As he spoke, he 
filled huge empty tracts on Brad’s mental map of the financial 
markets. “What he said told me that we needed to care about 
microseconds and nanoseconds,” said Brad. The U.S. stock mar- 
ket was now a class system, rooted in speed, of haves and have- 
nots. The haves paid for nanoseconds; the have-nots had no idea 
that a nanosecond had value. The haves enjoyed a perfect view 
of the market; the have-nots never saw the market at all. What had 
once been the world’s most public, most democratic, financial 
market had become, in spirit, something more like a private 
viewing of a stolen work of art. “I learned more from talking to 
him in an hour than I learned from six months of reading about 
HFT,” said Brad. “The second I met him I wanted to hire him.” 

He wanted to hire him without being able to fully explain, to 
his bosses or even to Ronan, what he wanted to hire him for. He 
couldn’t very well call him Vice President in Charge of Explain- 
ing to My Clueless Superiors Why High-Frequency Trading Is 
a Travesty. So he called him Head of High-Frequency Trading 
Strategies. “I felt he needed a ‘Head of’ title,” said Brad, “to get 



more respect from people.” That was Brad’s main concern: that 
people on the trading floor, even at RBC, would take one look 
at Ronan and see a guy in a yellow jumpsuit who’d just emerged 
from some manhole. Ronan didn’t even pretend to know what 
happened on a trading floor. “He had questions that were unbe- 
lievably rudimentary but that were necessary,” said Brad. “He 
didn’t know what ‘bid’ and ‘offer’ was. He didn’t know what it 
meant to ‘cross the spread.’ ” 

On the side, without making a big deal of it, Brad started to 
teach Ronan the language of trading. A “bid” was an attempt 
to buy stock, an “offer” an attempt to sell it. To cross the spread, 
if you were selling, meant to accept the bidder’s price, or, if you 
were buying, the ottering price. “This fucking guy didn’t laugh 
at me,” said Ronan. “He sat down and explained it.” That was 
their private deal: Brad would teach Ronan about trading, and 
Ronan would teach Brad about technology. 

Right away there was something to teach. Brad and his team 
were having trouble turning Thor into a product they could 
sell to investors. The investors they’d told about their discov- 
ery were clearly eager to buy Thor and use it for themselves — 
T. Rowe Price’s Gitlin had more or less tried to buy it on the 
spot — but Thor now had its problems. The experiment of arriv- 
ing at the exchanges at the same time had worked perfectly — the 
first time. It proved hard to repeat, because it was difficult to 
coax thirteen light signals to arrive in thirteen different stock 
exchanges spread across northern New Jersey within 350 micro- 
seconds of each other — or roughly 100 microseconds less than 
the time they had calculated it would take some high-speed 
trader to front-run their order. They’d succeeded the first time 
by estimating the differences in travel time it took to send the 
messages to the various exchanges, and by building the equiva- 



lent delays into their software. But the travel times were never 
the same. They had no control over the path the signals took to 
get to the exchanges, or how much traffic was on the network. 
Sometimes it took 4 milliseconds for their stock market orders 
to arrive at the New York Stock Exchange; other times, it took 
7 milliseconds. When the travel time differed from their guesses 
of what it would be, the market, once again, vanished. 

In short, Thor was inconsistent; and it was inconsistent, Ronan 
explained, because the paths the electronic signals took from 
Brad’s desk to the various exchanges were inconsistent. Ronan 
could see that these traders hadn’t thought much about the phys- 
ical process by which their signals traveled to the New Jersey 
stock exchanges. “I realized very quickly,” he said, “and they’ll 
admit this, so I mean no disrespect, that they had no fucking 
clue what they were doing.” The signal sent from Brad’s desk 
arrived at the New Jersey exchanges at different times because 
some exchanges were farther from Brad’s desk than others. The 
fastest any high-speed trader’s signal could travel from the first 
exchange it reached to the next one was 465 microseconds, or 
one two-hundredths of the time it takes to blink your eye, if you 
have a talent for it. That is, for Brad’s trading orders to interact 
with the market as displayed on his trading screens, they needed 
to arrive at all the exchanges within a 465 -microsecond win- 
dow. The only way to do that, Ronan told his new colleagues at 
RBC, was to build and control your own fiber network. 

To make his point, Ronan brought in oversized maps of 
New Jersey showing the fiber-optic networks built by telecom 
companies. On the maps you could see just how a signal trav- 
eled from Brad’s trading station at One Liberty Plaza to the 
exchanges. When he unrolled his first map, a guy who worked 
in RBC’s network support team burst out, “How the fuck did 



you get those? They’re telecom property! They’re proprietary!” 
Ronan explained, “When they said they wouldn’t give them to 
me because they were proprietary, I said, Well, then, propri- 
etarily fuck off.’ ” The high-frequency traders were paying the 
telecom carriers too much to be denied whatever they wanted, 
and Ronan had been the agent of their desires. “These maps are 
like fucking gold,” he said. “But I had brought them so much 
business that they would let me see inside their freaking wife’s 
underwear drawer if I asked them to.” 

The maps told a story: Any trading signal that originated in 
lower Manhattan traveled up the West Side Highway and out 
the Lincoln Tunnel. Perched immediately outside the tunnel, in 
Weehawken, New Jersey, was the BATS exchange. From BATS 
the routes became more complicated, as they had to find their 
way through the clutter of the Jersey suburbs. “New Jersey is 
now carved up like a Thanksgiving turkey,” said Ronan. One 
way or another, they traveled east to Secaucus, the location of 
the Direct Edge family of exchanges founded by Goldman Sachs 
and Citadel, and south to the Nasdaq family of exchanges in 
Carteret. The New York Stock Exchange further complicated 
the story. In early 2010, NYSE still had its computer servers in 
lower Manhattan, at 55 Water Street. (They moved them to 
distant Mahwah, New Jersey, that August.) As it was less than a 
mile from Brad’s desk, NYSE appeared to be the stock market 
closest to him; but Ronan’s maps showed the incredible indirec- 
tion of optic fiber in Manhattan. “To get from Liberty Plaza 
to Fifty-five Water Street, you might go through Brooklyn,” 
he explained. “You can go fifty miles to get from Midtown to 
downtown. To get from a building to a building across the street 
you could travel fifteen miles.” It was a ten-minute walk from 
RBC’s office at Liberty Plaza to the New York Stock Exchange. 



But from a computer’s point of view, the New York Stock 
Exchange was further from RBC’s offices than Carteret. 

To Brad the maps explained, among other things, why the 
market on BATS had proved so accurate. The reason they were 
always able to buy or sell 100 percent of the shares listed on 
BATS was that BATS was always the first stock market to receive 
their orders. News of their buying and selling hadn’t had time 
to spread throughout the marketplace. “I was like, ‘Holy shit, 
BATS is just closest to us.’ It’s right outside the freaking tunnel.” 
Inside BATS, high-frequency trading firms were waiting for 
news that they could use to trade on the other exchanges. They 
obtained that news by placing very small bids and offers, typi- 
cally for 100 shares, for every listed stock. Having gleaned that 
there was a buyer or seller of Company X’s shares, they would 
race ahead to the other exchanges and buy or sell accordingly. 
(The race they needed to win was not a race against the ordi- 
nary investor, who had no clue what was happening to him, but 
against other high-speed traders.) The orders resting on BATS 
were typically just the 100-share minimum required for an 
order to be at the front of any price queue, as their only purpose 
was to tease information out of investors. The HFT firms posted 
these tiny orders on BATS — orders to buy or sell 100 shares of 
basically every stock traded in the U.S. market — not because 
they actually wanted to buy and sell the stocks but because they 
wanted to find out what investors wanted to buy and sell before 
they did it. BATS, unsurprisingly, had been created by high- 
frequency traders. 

The funny thing was that a lot of what Ronan had seen and 
heard didn’t make sense to him: He didn’t know what he knew. 
Brad now helped him to understand. For instance, Ronan had 
noticed the HFT guys creating elaborate tables of the time, 



measured in microseconds, it took for a stock market order to 
travel from any given brokerage house to each of the exchanges. 

Latency tables,” these were called. The times were subtly differ- 
ent for every brokerage house — they depended upon where the 
brokerage house physically was located and which fiber networks 
it leased in New Jersey. These tables took trouble to create and 
were of obvious value to high-frequency traders, but Ronan had 
no idea why. This was the first Brad had heard of latency tables, 
but he knew exactly why they had been created: They enabled 
high-frequency traders to identify brokers by the time their 
orders took to travel from one exchange to the other. Once you 
had figured out which broker was behind any given stock mar- 
ket order, you could discern patterns in each broker’s behavior. 
If you knew which broker had just come into the market with 
an order to buy 1,000 shares of IBM, you might further guess 
whether those 1,000 shares were the entire order or a part of a 
much larger order. You might also guess how the broker might 
distribute the order among the various exchanges and how much 
above the current market price for IBM shares the broker might 
be willing to pay. The HFT guys didn’t need perfect informa- 
tion to make riskless profits; they only needed to skew the odds 
systematically in their favor. But, as Brad put it, “What you’re 
looking for ultimately is large brokers who are behaving idioti- 
cally with their customers’ orders. That’s the real gold mine.” 

He also knew that Wall Street brokers had a new incentive 
to behave idiotically, because he had himself succumbed to the 
temptation. When Wall Street decided where to route their cli- 
ents’ stock market orders, they were now greatly influenced by 
the new system of kickbacks paid and fees charged to them by the 
exchanges: If a big Wall Street broker stood to be paid to send an 
order to buy 10,000 shares of IBM to BATS but was charged to 



send the same order to the New York Stock Exchange, it would 
program its routers to send the customer’s order to BATS. The 
router, designed by human beings, took on a life of its own. 

Along with the trading algorithms, the routers were a criti- 
cal piece of technology in the automated stock markets. Both 
are designed and built by people who work for the Wall Street 
broker. Both do the thinking that people used to do, but the 
intellectual tasks they perform are different. The algorithm does 
its thinking first: It decides how to slice up any given order. 
Say you want to buy 100,000 shares of XYZ Company at no 
more than $25 a share, when the market shows a total of 2,000 
shares offered at $25. To simply attempt to buy 100,000 shares 
all at once would create havoc in the market and drive the price 
higher. The algorithm decides how many shares you buy, when 
to buy them, and the price to pay. For example, it may instruct 
the router to carve the 100,000-share order into twenty pieces, 
and to buy 5,000 shares every five minutes, so long as the price 
is no higher than $25. 

The router determines where the order is sent. For instance, a 
router might instruct the order to go first to a Wall Street firm’s 
dark pool before going to the exchanges. Or it might instruct the 
order to go first to any exchange that will pay the broker to trade, 
and only then to exchanges on which the broker will be compelled 
to pay to trade. (This is a so-called sequential cost-effective router.) 
To illustrate how stupid routing can be, say you have told your 
Wall Street broker — to whom you are paying a commission — that 
you wish to buy 100,000 shares of Company XYZ at $25 and 
now, conveniently, there are 100,000 shares for sale at $25, 10,000 
on each of ten different exchanges, all of which will charge the 
broker to trade on your behalf (though far less than the com- 
mission you have paid to him). There are, however, another 100 



shares for sale, also at $25, on the BATS exchange — which will 
pay the broker for the trade. The sequential cost-effective router 
will go first to BATS and buy the 100 shares — and cause the other 
100,000 shares to vanish into the paws of high-frequency trad- 
ers (in the bargain relieving the broker of the obligation to pay 
to trade). The high-frequency traders can then turn around and 
sell the shares of Company XYZ at a higher price, or hold onto 
the shares for a few seconds more, while you, the investor, chase 
Company XYZ’s shares even higher. In either case, the result is 
unappealing to the original buyer of Company XYZ’s shares. 

That is but the most obvious of many examples of routing stu- 
pidity. The customer (you, or someone investing on your behalf) 
is typically entirely oblivious to the inner workings of both algo- 
rithms and routers: Even if he demanded to know how his order 
was routed, and his broker told him, he would never be sure what 
was said was true, as he has no sufficiently detailed record of what 
shares traded and when they traded. 

The brokers’ routers, like bad poker players, all had a con- 
spicuous tell. The tell might be a glitch in their machines rather 
than a twitch of their facial muscles, but it was just as valuable to 
the HFT guys on the other side of the table. 

Once Brad had explained all of this to Ronan, he didn’t need 
to explain it again. “It was, ‘Oh shit, some of the things I over- 
heard now make more sense,’ ” said Ronan. 

With Ronan’s help, the RBC team designed their own fiber 
network and turned Thor into a product that could be sold to 
investors. The sales pitch was absurdly simple: There is a new 
predator in the financial markets. Here is how he operates, and we have 
a weapon you can use to defend yourself against him. The argument 
about whether RBC should leap into bed with high-frequency 
traders ended. Brad’s new problem was spreading the word of 



what he now knew to the U.S. investing public. Seeing how 
shocked people were by what Ronan had to say, and how inter- 
ested they were in it, and no longer needing Ronan to per- 
suade his bosses that something strange and new was afoot, Brad 
decided to set Ronan loose on Wall Street’s biggest customers. 
“Brad calls me in and says, ‘What if we stop calling you Head of 
High-Frequency Trading Strategy and make you Head of Elec- 
tronic Trading Strategy?,’ ” said Ronan, who had no idea what 
either title actually meant. “I called my wife and said, ‘I think 
they just promoted me.’ ” 

A few days later, Ronan went with Brad to his first Wall 
Street meeting. “Right before the meeting, Brad says, ‘What 
are you going to say? What have you prepared?’ I hadn’t pre- 
pared anything, so I said, ‘I’ll just wing it.’ ” He now had a 
pretty good idea why Brad had given him a new job title. “My 
role was to walk around and say to clients, ‘Don’t you under- 
stand you’re being fucked?’ ” The man on the other end of this 
first extemporaneous presentation — the president of a $9 billion 
hedge fund — recalls the encounter this way: “I know I have a 
three-hundred-million-dollar problem on a nine-billion-dollar 
hedge fund.” (That is, he knows that the cost of not being 
able to trade at the stated market prices is costing him $300 
million a year.) “But I don’t know exactly what the problem 
is. As he’s talking, I’m saying to myself, RBC doesn’t even 
know what they are doing. And who are these guys? They 
aren’t traders. They’re not salesguys. And they’re not quants. 
So what are they? And then they say they have a solution to the 
world’s problems. And you’re like: ‘What? How on earth can 
I even trust you?’ And then they totally explain my problem.” 
Between them, Brad and Ronan told this hedge fund manager 
all they had learned. They explained, in short, how the infer- 



mational value of everything this man did with money was 
being auctioned by brokers and exchanges to high-frequency 
trading firms so that they might exploit him. That was why he 
had a $300 million problem on a $9 billion fund. 

After Brad and Ronan had left his office, the president of 
this big hedge fund, who had never before thought of himself 
as prey, reconsidered the financial markets. He sat at his desk 
watching both his personal online brokerage account and his 
$l,800-a-month Bloomberg terminal. In his private brokerage 
account he set out to buy an exchange-traded fund (ETF) com- 
prised of Chinese construction companies. Over several hours 
he watched the price of the fund on his Bloomberg terminal. 
It was midnight in China, nothing was happening, and the 
ETF’s price didn’t budge. He then clicked the Buy button on his 
online brokerage account screen, and the price on the Bloom- 
berg screen jumped. Most people who used online brokerage 
accounts didn’t have Bloomberg terminals that enabled them 
to monitor the market in something close to real time. Most 
investors never would know what happened in the market after 
they pressed the Buy button. “I hadn’t even hit Execute,” says 
the hedge fund president. “I hadn’t done anything but put in a 
ticker symbol and a quantity to buy. And the market popped.” 
Then, after he had bought his ETF at a higher price than origi- 
nally listed, the hedge fund president received a confirmation 
saying that the trade had been executed by Citadel Derivatives. 
Citadel was one of the biggest high-frequency trading firms. 
“And I wondered, Why is my online broker sending my trades 
to Citadel?” 

Brad had observed and encouraged a lot of Wall Street careers, 
but, as he said, “I’d never seen anyone’s star rise as quickly as 
Ronan’s did. He just took off.” Ronan, for his part, couldn’t 



quite believe how ordinary the people on Wall Street were. “It’s 
a whole industry of bullshit,” he said. The first thing that struck 
Ronan about a lot of the big investors he met was their inse- 
curity. “People in this industry don’t want to admit they don’t 
know something,” he said. “Almost never do they say, ‘No, I 
don’t know. Tell me.’ I’d say, ‘Do you know what co-location 
is?’ And they’d say, ‘Oh yeah, I know about co-location.’ Then 
I’d say, ‘You know, HFT now puts their servers in the same 
building with the exchange, as close as possible to the exchange’s 
matching engine, so they get market data before everyone else.’ 
And people are like, ‘What the fuck??!! That’s got to be illegal!’ 
We met with hundreds of people. And no one knew about it.” 
He was also surprised to find how wedded they were to the big 
Wall Street banks, even when those banks failed them. “In HFT 
there was no loyalty whatsoever,” he said. Over and over again, 
investors would tell Ronan and Brad how outraged they were 
that the big Wall Street firms that handled their stock market 
orders had failed to protect them from this new predator. Yet 
they were willing to give RBC only a small percentage of their 
trades to execute. “This was the biggest confusion to me about 
Wall Street,” said Ronan. “ ‘Wait, you’re telling me you can’t 
pay us because you need to pay all these other people who are 
trying to screw you?’ ” 

Maybe because Ronan was so unlike a Wall Street person, he 
was granted special access and was able to get inside the heads of 
the Wall Street people to whom he spoke. “After that first meet- 
ing, I told him there was no point in us even being in the same 
meeting,” said Brad. “We needed to divide and conquer.” 

By the end of 2010, Brad and Ronan between them met with 
roughly five hundred professional stock market investors who 
controlled, among them, many trillions of dollars in assets. They 



never created a PowerPoint; they never did anything more for- 
mal than sit down and tell people everything they knew in plain 
English. Brad soon realized that the most sophisticated investors 
didn’t know what was going on in their own market. Not the 
big mutual funds, Fidelity and Vanguard. Not the big money 
management firms like T. Rowe Price and Janus Capital. Not 
even the most sophisticated hedge funds. The legendary inves- 
tor David Einhorn, for instance, was shocked; so was Dan Loeb, 
another prominent hedge fund manager. Bill Ackman ran a 
famous hedge fund, Pershing Square, that often made bids for 
large chunks of companies. In the two years before Brad turned 
up in his office to explain what was happening, Ackman had 
started to suspect that people might be using the information 
about his trades to trade ahead of him. “I felt that there was a 
leak every time,” says Ackman. “I thought maybe it was the 
prime broker. It wasn’t the kind of leak that I thought.” A sales- 
man Brad hired at RBC from Merrill Lynch to help him mar- 
ket Thor recalls one big investor calling to say, “You know, 
I thought I knew what I did for a living but apparently not, 
because I had no idea this was going on.” 

Then came the so-called flash crash. At 2:45 on May 6, 2010, 
for no obvious reason, the market fell six hundred points in a 
few minutes. A few minutes later, like a drunk trying to pre- 
tend he hadn’t just knocked over the fishbowl and killed the 
pet goldfish, it bounced right back up to where it was before. If 
you weren’t watching closely you could have missed the entire 
event — unless, of course, you had placed orders in the mar- 
ket to buy or sell certain stocks. Shares of Procter & Gamble, 
for instance, traded as low as a penny and as high as $100,000. 
Twenty thousand different trades happened at stock prices more 
than 60 percent removed from the prices of those stocks just 



moments before. Five months later, the SEC published a report 
blaming the entire fiasco on a single large sell order, of stock 
market futures contracts, mistakenly placed on an exchange in 
Chicago by an obscure Kansas City mutual fund. 

That explanation could only be true by accident, because the 
stock market regulators did not possess the information they 
needed to understand the stock markets. The unit of trading 
was now the microsecond, but the records kept by the exchanges 
were by the second. There were one million microseconds in 
a second. It was as if, back in the 1920s, the only stock market 
data available was a crude aggregation of all trades made during 
the decade. You could see that at some point in that era there 
had been a stock market crash. You could see nothing about the 
events on and around October 29, 1929. The first thing Brad 
noticed as he read the SEC report on the flash crash was its old- 
fashioned sense of time. “I did a search of the report for the word 
‘minute,’ ” said Brad. “I got eighty-seven hits. I then searched for 
‘second’ and got sixty-three hits. I then searched for ‘millisec- 
ond’ and got four hits- — none of them actually relevant. Finally, 
I searched for ‘microsecond’ and got zero hits.” He read the 
report once and then never looked at it again. “Once you get a 
sense of the speed with which things are happening, you realize 
that explanations like this — someone hitting a button — are not 
right,” he said. “You want to see a single time-stamped sheet of 
every trade. To see what followed from what. Not only does it 
not exist, it can’t exist, as currently configured.” 

No one could say for sure what caused the flash crash — for 
the same reason no one could prove that high-frequency traders 
were front-running the orders of ordinary investors. The data 
didn’t exist. But Brad sensed that the investment community 
was not persuaded by the SEC’s explanation and by the assur- 



ances of the stock exchanges that all was well inside them. A 
lot of them asked the same question he was asking himself: Isn’t 
there a much deeper question of how this one snowball caused 
a deadly avalanche? He watched the most sophisticated inves- 
tors respond after Duncan Niederauer, the CEO of the New 
York Stock Exchange, embarked on a goodwill tour, the pur- 
pose of which seemed to be to explain why the New York Stock 
Exchange had nothing to do with the flash crash. “That’s when 
a light went off,” said Danny Moses, of Seawolf Capital, a hedge 
fund that specialized in stock market investments. He had heard 
Brad and Ronan’s pitch. “Niederauer was saying, ‘Hey, have 
confidence in us. It wasn’t us.’ Wait a minute: I never thought it 
was you. Why should I be concerned that it was you? It was like 
your kid walks into your house and says to you, ‘Dad, I didn’t 
dent your car.’ Wait, there’s a dent in my car?” 

After the flash crash, Brad no longer bothered to call investors 
to set up meetings. His phone rang off the hook. “What the flash 
crash did,” said Brad, “was it opened the buy side’s willingness 
to understand what was going on. Because their bosses started 
asking questions. Which meant that our telling the truth, and 
explaining it to them, fit perfectly.” 

A few months later, in September 2010, another strange, 
albeit more obscure, market event occurred, this time in the 
Chicago suburbs. A sleepy stock exchange called the CBSX, 
which traded just a tiny fraction of total stock market volume, 
announced that it was going to invert the usual system of fees 
and kickbacks. It was now going to pay people to “take” liquid- 
ity and charge people to “make” it. Once again, this struck Brad 
as bizarre: Who would make markets on exchanges if they had 
to pay to do it? But then the CBSX exploded with activity. 
Over the next several weeks, for example, it handled a third of 



the total volume of the shares traded in Sirius, the satellite radio 
company. Brad knew that Sirius was a favorite stock of HFT 
firms — but he couldn’t understand why it was suddenly trading 
in huge volume in Chicago. Obviously, when they saw they 
could be paid to “take” on the CBSX, the big Wall Street bro- 
kers all responded by reprogramming their routers so that their 
customers’ orders were sent to the CBSX. But who was on the 
other side of their trades, paying more than ever had been paid 
for the privilege? 

That’s when Ronan told Brad about a new company called 
Spread Networks. Spread Networks, as it turned out, had tried 
to hire Ronan to sell its precious line to high-frequency trad- 
ers. They’d walked Ronan through their astonishing tunneling 
project and their business plans. “I told them they were fucking 
bananas,” said Ronan. “They said they were going to sell two 
hundred of these things. I came up with a list of twenty-eight 
firms who would potentially buy the line. Plus they were charg- 
ing ten point six million dollars up front for five years’ worth of 
service, and they wanted to pay me twelve grand for each one I 
sold. Which is just an insult. You might as well ask me to blow 
you while I’m doing it.” 

Ronan mentioned this unpleasant experience to Brad, who 
naturally said, “You’re telling me this nouP.” Ronan explained 
that he hadn’t been able to mention Spread before because he 
had signed a non-disclosure agreement with the company. The 
agreement had expired that day, and so now he was free to dis- 
close not only what Spread had done but for whom they had 
done it: not just HFT firms like Knight and Citadel but also the 
big Wall Street banks — Morgan Stanley, Goldman Sachs, and 
others. “You couldn’t prove what these guys were doing was a 
big deal, because they were so guarded about how much money 



they were making,” said Brad. “But you could see how big a 
deal it was by how much they spent. And now the banks were 
involved. I thought, Oh shit, this isn’t just HFT shops. This is 
industry-wide. It’s systemic.” 

Ronan offered an explanation for what had just happened on 
the CBSX: Spread Networks had flipped its switch and turned 
itself on just two weeks earlier. CBSX then inverted its pricing. 
By inverting its pricing — by paying brokers to execute custom- 
ers’ trades for which they would normally be charged a fee— the 
exchange enticed the brokers to send their customers’ orders to 
the CBSX so that they might be front-run back to New Jersey 
by high-frequency traders using Spread Networks. The infor- 
mation that high-frequency traders gleaned from trading with 
investors in Chicago they could use back in the markets in New 
Jersey. It was now very much worth it to them to pay the CBSX 
to “make” liquidity. It was exactly the game they had played on 
BATS, of enticing brokers to reveal their customers’ intentions 
so that they might exploit them elsewhere. But racing a cus- 
tomer order from Weehawken to other points in New Jersey was 
hard compared to racing it from Chicago on Spread’s new line. 

Spread was another piece of what was becoming a fantastically 
elaborate puzzle. The team Brad was assembling at RBC didn’t 
have all the pieces to the puzzle — not yet — but they had more 
of them than anyone else willing to talk openly on the sub- 
ject. The reactions of investors to what they already knew they 
considered as simply more pieces of the puzzle. Every now and 
then — perhaps 5 percent of the time — Brad or Ronan met some 
investor who didn’t care to know about the puzzle, someone 
who didn’t want to hear their story. Whenever Brad returned 
from one of these meetings, he’d discover that the person to 
whom he had just spoken depended, one way or another, on 



the revenues flowing to high-frequency traders. Every now and 
again — maybe another 5 percent of the time — they met with 
an investor who was completely terrified. “They knew so little, 
and they’d be so scared inside their own firms that they’d rather 
the meeting never happened,” said Brad. But most of the hun- 
dreds of big-time investors with whom Brad and Ronan spoke 
had the same reaction as T. Rowe Price’s Mike Gitlin: They 
knew something was very wrong, but they didn’t know what, 
and now that they knew they were outraged. “Brad was the 
honest broker,” said Gitlin. “1 don’t know how many knew it, 
but he was the only guy who would say it. He was saying, ‘I’m 
here and I’m watching it and we’re a party to it and the whole 
thing is rigged.’ He exposed people who were bad actors, and 
a lot of people in this industry are afraid to do that. He was 
saying, ‘This is just offensive.’ ” Vincent Daniel, the head strate- 
gist at Seawolf, put it another way. He took a long look at this 
unlikely pair — a Canadian Asian guy from this bank no one 
cared about, and this Irish guy who was doing a fair impres- 
sion of a Dublin handyman — who had just told him the most 
incredible true story he had ever heard, and said, “Your biggest 
competitive advantage is that you don’t want to fuck me.” 

Trust on Wall Street was still — just — possible. The big inves- 
tors who trusted Brad began to share whatever information they 
could get their hands on from their other brokers — information 
Brad was never meant to see. For instance, several demanded to 
know from their other Wall Street brokers what percentage of the 
trades executed on their behalf were executed inside the brokers’ 
dark pools. These dark pools contained the murkiest financial 
incentives in the new stock market. Goldman Sachs and Credit 
Suisse ran the most prominent dark pools. But every brokerage 
firm strongly encouraged investors who wanted to buy or sell 



big chunks of stock to do so in that firm’s dark pool. In theory, 
the brokers were meant to find the best price for their custom- 
ers. If the customer wanted to buy shares in Chevron, and the 
best price happened to be on the New York Stock Exchange, the 
broker was not supposed to stick the customer with a worse price 
inside their dark pool. But the dark pools were opaque. Their 
rules were not published. No outsider could see what went on 
inside them. It was entirely possible that a broker’s own traders 
were trading against the customers in the dark pool: There were 
no rules against it. And while the brokers often protested that 
there were no conflicts of interest inside their dark pools, all the 
dark pools exhibited the same strange property: A huge percent- 
age of the customer orders sent into a dark pool were executed 
inside the pool. Brad knew this because a handful of the world’s 
biggest stock market investors had shared their information with 
him — so that he might help them figure out what was going on. 

It was hard to explain. A broker was expected to find the 
best possible price in the market for his customer. The Goldman 
Sachs dark pool — to take one example — was less than 2 percent 
of the entire stock market. So why did nearly 50 percent of the 
customer orders routed into Goldman’s dark pool end up being 
executed inside that pool — rather than out in the wider market? 
Most of the brokers’ dark pools constituted less than 1 percent of 
the entire market, and yet somehow those brokers found the best 
price for their customers between 15 and 60 percent of the time. 
(So-called rates of internalization varied from broker to broker.) 
And because the dark pool was not required to say exactly when 
it had executed a trade, and the broker did not typically tell his 
investors where it had executed a trade, much less the market 
conditions at the moment of execution, the customer lived in 
darkness. Even a giant investor like T. Rowe Price simply had to 



take it on faith that Goldman Sachs or Merrill Lynch had acted 
in its interest, despite the obvious financial incentives not to do 
so. As Mike Gitlin said, “It’s just very hard to prove that any 
broker-dealer is routing the trades to someplace other than the 
place that is best for you. You couldn’t SEE what any given bro- 
ker was doing.” If an investor as large as T. Rowe Price, which 
acted on behalf of millions of small investors, was unable to 
obtain from its stockbrokers the information it needed to deter- 
mine if the brokers had acted in their interest, what chance did 
the little guy have? 

In this environment, the effect of trying to help investors see 
what was happening to their money was revolutionary. The 
Royal Bank of Canada had never been anything more than the 
most trivial player in the U.S. stock market. At the end of 2010, 
Brad saw a report from Greenwich Associates, the firm used by 
Wall Street banks to evaluate their standing in relation to their 
peers. Greenwich Associates interviews the investors who use 
Wall Street’s services and privately reports their findings to the 
Wall Street firms. In 2009, RBC had — at number 19 — been far 
down Greenwich Associates’ stock market rankings. At the end 
of 2010, after only six months of Thor, RBC was ranked num- 
ber 1. Greenwich Associates called RBC to ask what on earth 
was going on within the bank. In the history of their rankings, 
they said, they had never seen a firm jump more than three spots. 

At the same time, this movement spawned by Brad Kat- 
suyama’s unhappiness with Wall Street was starting to feel less 
like a business than a cause. Brad was no radical. As he put it, 
“There’s a difference between choosing a crusade and having it 
thrust on you.” He’d never really thought all that much about 
how he fit into the bigger picture, and certainly never consid- 
ered himself a character upon a stage. He’d never run for stu- 



dent council. He’d never had anything to do with politics. “It’s 
always seemed to me that the things you need to do to influ- 
ence change had to do with glad-handing,” he said. “It just felt 
so phony.” This didn’t feel phony. This felt like a situation in 
which a person, through his immediate actions, might change 
the world. After all, he was now educating the world’s biggest 
money managers about the inner workings of the stock market, 
which strongly suggested to him that no one else on Wall Street 
was willing to teach them how their investment dollars were 
being abused. The more he understood the inner workings of 
the financial system, the better he might inform the investors, 
big and small, who were being abused by that system. And the 
more pressure they might bring to bear on the system to change. 

The deep problem with the system was a kind of moral iner- 
tia. So long as it served the narrow self-interests of everyone 
inside it, no one on the inside would ever seek to change it, no 
matter how corrupt or sinister it became — though even to use 
words like “corrupt” and “sinister” made serious people uncom- 
fortable, and so Brad avoided them. Maybe his biggest concern, 
when he spoke to investors, was that he’d be seen as just another 
nut with a conspiracy theory. One of the compliments that made 
him happiest was when a big investor said, “Thank God, finally 
there’s someone who knows something about high-frequency 
trading who isn’t an Area 51 guy.” Because he wasn’t a radical, 
it took him a while to figure out that fate and circumstance had 
created for him a dramatic role, which he was obliged to play. 
One night he actually turned to Ashley, now his wife, and said, 
“It feels like I’m an expert in something that badly needs to be 
changed. I think there’s only a few people in the world who can 
do anything about this. If I don’t do something right now — me, 
Brad Katsuyama — there’s no one to call.” 



B y the end of 2010 they’d built a marketable weapon. The 
weapon promised to defend investors in the U.S. stock 
market from what appeared to be a new kind of mar- 
ket predator. About that predator they knew surprisingly little. 
Apart from Ronan, Brad knew no one from inside the world 
of high-frequency trading. He had only a vague idea of that 
world’s reach, or its political influence. From Ronan he knew 
that the HFT firms enjoyed special relationships with the public 
stock exchanges, but he knew nothing about their dealings with 
the big Wall Street banks tasked with guarding the interests of 
investors. Then again, many of the people who worked inside 
the Wall Street banks seemed to have only the faintest idea of 
what those banks were up to. If you worked for a big Wall Street 
bank, the easiest way to find out what other banks were up to 
was to seek out their employees who were looking for new jobs 
and interview them. In the wake of the financial crisis, the too- 
big-to-fail end of Wall Street was in turmoil, and Brad was able 



to talk to people who, just a few years before, would never have 
considered working for the Royal Bank of Canada. By the time 
he was finished picking their collective brains, he had spoken 
to more than a hundred employees at too-big-to-fail banks but 
hired only about thirty-five of them. “They all wanted jobs,” 
he said. “It’s not that they wouldn’t tell me. It’s that they didn’t 
know how their own electronic systems worked.” 

The thread running through all these people, even the ones he 
didn’t hire, was their fear and distrust of the system. John Schwab 
was a curious case in point. Schwab’s father had been a firefighter 
on Staten Island, like his father before him. “Every male on my 
father’s side is a fireman,” Schwab said. “I wanted to do some- 
thing more.” More meant getting a master’s in engineering from 
the Stevens Institute of Technology, in Hoboken, New Jersey. In 
the late 1990s he took a job at Banc of America Securities,* where 
he rose to a position with an important-sounding title: Head of 
New Products. His job description was more glamorous than his 
job. John Schwab was the guy behind the scenes who handled 
the boring details, like managing relations between the traders on 
the floor and the tech geeks who built stuff for them, or ensuring 
that the bank complied with new stock market regulations. He 
routinely ranked in the top 1 percent of all employees in Banc of 
America’s reviews of its personnel, but his status in a Wall Street 
bank was akin to head butler to a British upper-class family. To 
the grunts in the back office he might have seemed like a big 
shot, but to the traders who made the money he did not. 

* It is irritating to read about an American bank that insists on calling itself a banc. The 
banc in this case was pushed to do so, as the securities divisions within American banks 
(here, Bank of America) are prohibited by regulators from referring to themselves as 



Whatever frustration this caused him he buried. Given an 
excuse to feel loyalty for his company, he seized it. September 
11, 2001, for instance. Schwab’s desk was in the North Tower 
of the World Trade Center, on the eighty-first floor. By sheer 
fluke he had been late to work that morning — the only day in 
2001 he would report late to work — and he’d watched the first 
plane hit, thirteen floors above his desk, from the window of a 
distant bus. Several of his colleagues died that day, and so had 
some Staten Island firemen he’d known. Schwab seldom spoke 
of the event, but privately he believed that, had he been at his 
desk when the plane hit, his instinct would have been to go up 
the stairs rather than down them. The guilt he felt for not having 
been on hand to help somehow became, in his mind, a debt he 
owed to his colleagues and to his employer. Which is to say that 
Schwab wanted to feel toward a Wall Street bank what a fireman 
is meant to feel toward his company. “I thought I’d be at Banc of 
America forever,” he said. 

Then came the financial crisis, and, in 2008, the acquisition, 
by Bank of America, of a collapsing Merrill Lynch. What hap- 
pened next upended Schwab’s worldview. Merrill Lynch had 
been among the most prolific creators of the very worst sub- 
prime mortgage bonds. Had they been left to the mercy of the 
market — had Bank of America not saved them — the Merrill 
Lynch people would have been tossed out on the street. Instead, 
right before their acquisition, they awarded themselves massive 
bonuses that Bank of America wound up having to pay. “It was 
incredibly unfair,” said Schwab. “It was incredibly unjust. My 
stock in this company I helped to build for nine years goes into 
the shitter, and these assholes pay themselves record bonuses. It 
was a fucking crime.” Even more incredibly, the Merrill Lynch 
people ended up in charge of Bank of America’s equity division 


and set about firing most of the people in it. A lot of those people 
had been good, loyal employees of the bank. “Wall Street is cor- 
rupt, I decided,” said Schwall afterwards. “There is no corporate 
loyalty to employees.” 

Schwall was one of the few Banc of America people who 
kept his job: Merrill Lynch had no one to replace him. He hid 
his true feelings, but he no longer trusted his employer. And he 
sensed, for the first time in his career, that his employer did not 
trust him. One day he sent himself an email from his personal 
account to his work account — he was helping out some friends 
who had been fired by the bank and who wanted to start a 
small brokerage firm. His boss called him to ask him about it. 
What the hell are they doing monitoring my incoming emails? Schwall 

His ability to monitor his superiors exceeded their ability 
to monitor him, and he began to do it. “There was a lot of 
unspoken animosity,” he said. He noticed the explosion of trad- 
ing activity inside of Merrill Lynch’s dark pool fueled by high- 
frequency traders. He saw that Merrill Lynch created a new 
revenue line, to account for the money paid to them by high- 
frequency trading firms for access to the Merrill Lynch dark 
pool. He noticed that the guy who had built the Merrill Lynch 
electronic trading platform was one of the highest-paid people 
in all of Merrill Lynch — and he’d nevertheless quit to create a 
company that would cater to HFT firms. He noticed letters sent 
on bank letterhead to the Securities and Exchange Commission 
arguing against further stock market regulation. He saved one in 
which the bank’s lawyers wrote that “despite numerous changes 
in recent years in both market structure and participant behav- 
ior, the equity market is functioning well today.” One day he 
heard a rumor that the Merrill people had assigned an analyst to 



produce a report to prove that Merrill’s stock market customers 
were better off because of whatever happened inside Merrill’s 
dark pool. There was apparently some controversy around this 
report. Schwall filed that rumor away for later use. 

Schwall wanted to think of himself as a guy who lived by a 
few simple principles, a good soldier. After the financial cri- 
sis he was more like the Resentful Butler. He had a taste for 
asking complicated questions, and for tracking the answers into 
whatever rabbit hole they might lead him. He had, in short, an 
obsessive streak. 

It wasn’t until after he’d hired Schwall away from Bank of 
America to work for RBC that Brad noticed this side of Schwall. 
He should have seen it before, simply from Schwall’s chosen role 
on Wall Street: product manager. A product manager, to be any 
good, had to be obsessive. The role had been spawned by the 
widespread belief that traders didn’t know how to talk to com- 
puter geeks and that computer geeks did not respond rationally 
to big, hairy traders hollering at them. A product manager 
stood between the two groups, to sort out which of the things 
the traders wanted that were the most important and how 
best to build them. For instance, an RBC stock market trader 
might demand a button on his screen that said “Thor,” which 
he could hit when he wanted Thor to execute his order to buy 
stock. To design that button might require twenty pages of 
mind-numbingly detailed specifications. That’s where Schwall 
came in. “He goes into details that no one else will go into, 
because for some reason that’s what he likes to do,” said Brad. 

The first hint that Schwall’s obsession with detail might take a 
sharp turn into some private cul-de-sac came in company meet- 
ings. “He’d go off on complete tangents,” said Brad. “Semi- 
related but outer space— type stuff.” Another way Brad saw how 



Schwall’s mind worked was in a fight that Schwall picked not 
long after he started working at RBC. The bank had declined 
an offer to serve as a lead sponsor for a charity called Wings 
Over Wall Street. Wings Over Wall Street raised money to 
combat amyotrophic lateral sclerosis (ALS) — Lou Gehrig’s dis- 
ease. In response, and without explaining why, Schwall blasted 
a system-wide email explaining the importance of ALS research 
and encouraging all RBC employees to get behind Wings Over 
Wall Street. The RBC executives who had made the original 
decision understandably saw this rogue email as a political act 
intended to undermine their authority. For no apparent reason, 
Schwall had alienated a bunch of important people who had the 
power to fire him. 

Brad now found himself between his new, extremely valu- 
able employee and a top RBC executive who wanted his scalp. 
When pressed, Schwall finally explained to Brad that his mother 
had just died of ALS. “And he hadn’t thought to mention it,” 
said Brad. “He’d spent years trying to figure out how to help 
his mother. The fact his mother died of the disease would have 
won the argument, and he never mentions it. He said it would 
have been underhanded and unprincipled.” Schwall’s problem 
wasn’t an uncharming taste for corporate politics but a charming 
ineptitude at playing them, Brad decided. (“Anyone who was 
politically astute never would have done this.”) He neverthe- 
less stumbled into politics often enough and played them badly 
enough that Brad finally came up with a name for the resulting 
mess: a Schwalling. “A Schwalling is when he does something 
unintentionally idiotic that makes him look stupid,” said Brad. 

All Schwall would say is, “I just sort of get crazy from time 
to time.” He’d become obsessed with something, and his obses- 
sions sent him on a trip to a place from which the journey’s ori- 



gin could no longer be glimpsed. The result was a lot of activity 
without an obvious motive. 

Thor had triggered Schwab's private process. Thor, and what it 
implied about the U.S. financial system, became Schwall’s great- 
est obsession. Before Brad explained to him how Thor worked 
and why, Schwab hadn’t thought twice about the U.S. stock 
markets. After he met Brad, he was certain that the market at the 
heart of capitalism was rigged. “As soon as you realize this,” he 
said, “as soon as you realize that you are not able to execute your 
orders because someone else is able to identify what you are try- 
ing to do and race ahead of you to the other exchanges, it’s over,” 
he said. “It changes your mind.” He stewed on the situation; the 
longer he stewed, the angrier he became. “It really just pissed 
me off,” he said. “That people set out this way to make money 
from everyone else’s retirement account. I knew who was being 
screwed, people like my mom and pop, and I became hell-bent 
on figuring out who was doing the screwing.” He reconsidered 
what he’d seen at Merrill Lynch after they had taken over Bank 
of America’s stock trading department. He hunted down the 
analyst who had done the controversial analysis of Merrill’s dark 
pool, for instance. The analyst told him that he had found that 
the dark pool was actually costing the customers (while profit- 
ing Merrill Lynch), but that management did not want to hear it. 
“They kept on telling him to change his report,” said Schwab. 
“He was basically told that he had to find a different way to do 
it to get the answer they needed.” 

Early one Monday morning, in the summer of 2011, Brad had 
a cab from Schwab. “He said, ‘Hey, I’m not coming in today,’ ” 
recalls Brad. “And I said, ‘What’s going on?’ He just said, ‘Trust 
me.’ Then he disappeared.” 

The previous night Schwab had gone out into his backyard, 



with nothing but a cigar, a chair, and his iPad. “I had the belief 
that some people were perpetuating a fraud. When you think 
HFT, what do you think? You think nothing. You don’t have a 
person. You don’t have a face. You think a computer. But there are 
specific people behind this.” He’d started by Googling “front- 
running” and “Wall Street” and “scandal.” What he was looking 
for, at first, was the cause of the problem Thor had solved: How 
was it legal for a handful of insiders to operate at faster speeds 
than the rest of the market and, in effect, steal from investors? 
He soon had his answer: Regulation National Market System. 
Passed by the SEC in 2005 but not implemented until 2007, 
Reg NMS, as it became known, required brokers to find the 
best market prices for the investors they represented. The regu- 
lation had been inspired by charges of front-running made in 
2004 against two dozen specialists on the floor of the old New 
York Stock Exchange — a charge the specialists settled by paying 
a $241 million fine. 

Up till then the various brokers who handled investors’ stock 
market orders had been held to the loose standard of “best exe- 
cution.” What that meant in practice was subject to interpreta- 
tion. If you wanted to buy 10,000 shares of Microsoft at $30 a 
share, and the broker went into the market and saw that there 
were only 100 shares offered at $30, he might choose not to buy 
those hundred shares and wait until more sellers turned up. He 
had the discretion not to spook the market, and to play your 
hand on your behalf as smartly as he could. After the brokers 
abused the trust implicit in that discretion once too often, the 
government took the discretion away. Reg NMS replaced the 
loose notion of best execution with the tight legal one of “best 
price.” To define best price, Reg NMS relied on the concept 
of the National Best Bid and Offer, known as the NBBO. If 



an investor wished to buy 10,000 shares of Microsoft, and 100 
shares were offered on the BATS exchange at $30 a share, while 
the full 10,000 listed on the other twelve exchanges were offered 
at $30.01, his broker was required to purchase the 100 shares 
on Bats at $30 before moving on to the other exchanges. “It 
mandated routing to more exchanges than you might otherwise 
have to go to,” said Schwall. “And so it created more opportuni- 
ties for people to front-run you.” The regulation also made it far 
easier for high-frequency traders to predict where brokers would 
send their customers’ orders, as they must send them first to the 
exchange that offered the best market price. 

That would have been fine but for the manner in which the 
best market price was calculated. The new law required a mech- 
anism for taking the measure of the entire market — for creat- 
ing the National Best Bid and Offer — by compiling all the bids 
and offers for all U.S. stocks in one place. That place, inside 
some computer, was called the Securities Information Proces- 
sor, which, because there is no such thing on Wall Street as too 
many acronyms, became known as the SIP. The thirteen stock 
markets piped their prices into the SIP, and the SIP calculated 
the NBBO. The SIP was the picture of the U.S. stock market 
most investors saw. 

Like a lot of regulations, Reg NMS was well-meaning and 
sensible. If everyone on Wall Street abided by the rule’s spirit, 
the rule would have established a new fairness in the U.S. stock 
market. The rule, however, contained a loophole: It failed to spec- 
ify the speed of the SIP. To gather and organize the stock prices 
from all the exchanges took milliseconds. It took milliseconds 
more to disseminate those calculations. The technology used to 
perform these calculations was old and slow, and the exchanges 
apparently had little interest in improving it. There was no rule 



against high-frequency traders setting up computers inside the 
exchanges and building their own, much faster, better cared for 
version of the SIP. That’s exactly what they’d done, so well that 
there were times when the gap between the high-frequency 
traders view of the market and that of ordinary investors could 
be twenty-five milliseconds, or twice the time it now took to 
travel from New York to Chicago and back again. 

Reg NMS was intended to create equality of opportunity in 
the U.S. stock market. Instead it institutionalized a more perni- 
cious inequality. A small class of insiders with the resources to 
create speed were now allowed to preview the market and trade 
on what they had seen. 

Thus — for example — the SIP might suggest to the ordinary 
investor in Apple Inc. that the stock was trading at 400-400.01. 
The investor would then give his broker his order to buy 1,000 
shares at the market price, or $400.01. The infinitesimal period 
of time between the moment the order was submitted and the 
moment it was executed was gold to the traders with faster con- 
nections. How much gold depended on two variables: a) the gap 
in time between the public SIP and the private ones and b) how 
much Apple’s stock price bounced around. The bigger the gap 
in time, the greater the chance that Apple’s stock price would 
have moved; and the more likely that a fast trader could stick an 
investor with an old price. That’s why volatility was so valuable 
to high-frequency traders: It created new prices for fast traders 
to see first and to exploit. It wouldn’t matter if some people in 
the market had an early glimpse of Apple’s price if the price of 
Apple’s shares never moved. 

Apple’s stock moved a lot, of course. In a paper published in 
February 2013, a team of researchers at the University of Cali- 
fornia, Berkeley, showed that the SIP price of Apple stock and 



the price seen by traders with faster channels of market informa- 
tion differed 55,000 times in a single day. That meant that there 
were 55,000 times a day a high-frequency trader could exploit 
the SIP-generated ignorance of the wider market. Fifty-five 
thousand times a day, he might buy Apple shares at an outdated 
price, then turn around and sell them at the new, higher price, 
exploiting the ignorance of the slower-footed investor on either 
end of his trades. And that was only the most obvious way a 
high-frequency trader might use his advance view of the market 
to make money. 

Schwab already knew a lot about the boring nitty-gritty 
details of Reg NMS, as he had been in charge of implementing 
the new rule for the whole of Bank of America. He’d seen to 
the bank’s need to build so-called smart order routers that could 
figure out which exchange had the official best price of any 
given stock (the NBBO) and send the customers’ orders to that 
exchange. By complying with Reg NMS, he now understood, 
the smart order routers simply marched investors into various 
traps laid for them by high-frequency traders. “At that point I 
just got very, very pissed off,” he said. “That they are ripping off 
the retirement savings of the entire country through systematic 
fraud and people don’t even realize it. That just drives me up the 
fucking wall.” 

His anger expressed itself in a search for greater detail. When 
he saw that Reg NMS had been created to correct for the market 
manipulations of the old NYSE specialists, he wanted to know: 
How had that corruption come about? He began another search. 
He discovered that the New York Stock Exchange specialists 
had been exploiting a loophole in some earlier regulation — 
which of course just led Schwab to ask: What event had led the 
SEC to create that regulation? Many hours later he’d clawed his 



way back to the 1987 stock market crash, which, as it turned 
out, gave rise to the first, albeit crude, form of high-frequency 
trading. During the 1987 crash, Wall Street brokers, to avoid 
having to buy stock, had stopped answering their phones, and 
small investors were unable to enter their orders into the mar- 
ket. In response, the government regulators had mandated the 
creation of an electronic Small Order Execution System so that 
the little guy’s order could be sent into the market with the 
press of a key on a computer keyboard, without a stockbroker 
first taking it from him on the phone. Because a computer was 
able to transmit trades must faster than humans, the system was 
soon gamed by smart traders, for purposes having nothing to 
do with the little guy.* At which point Schwall naturally asked: 
From whence came the regulation that had made brokers feel 
comfortable not answering their phones in the midst of the 1987 
stock market crash? 

As it turns out, when you Google “front-running” and “Wall 
Street” and “scandal,” and you are hell-bent on following the 
search to its conclusion, the journey cannot be finished in an 
evening. At five o’clock Monday morning Schwall finally went 
back inside his house. He slept for two hours, then rose and 
called Brad to tell him he wasn’t coming to work. Then he set 
off for a Staten Island branch of the New York Public Library. 
“There was quite a bit of vengeance on my mind,” he said. As 
a high school junior Schwall had been New York City’s wres- 
tling champion in the 119-pound division. “He’s the nicest guy 
in the world most of the time,” said Brad. “But then sometimes 
he’s not.” A streak of anger ran through him, and exactly where 

* A year later, in 2012, Wall Street Journal reporter Scott Patterson would write an excel- 
lent history of the early electronic traders called Dark Pools. 



it came from Schwall could not say, but he knew perfectly well 
what triggered it: injustice. “If I can fix something and fuck 
these people who are fucking the rest of this country, I’m going 
to do it,” he said. The trigger for his most recent burst of feel- 
ing was Thor, but if you had asked him on Wednesday morning 
why he was still digging around the Staten Island library instead 
of going to work, Schwall wouldn’t have thought to mention 
Thor. Instead he would have said, “I am trying to understand 
the origins of every form of front-running in the history of the 
United States.” 

Several days later he’d worked his way back to the late 1800s. 
The entire history of Wall Street was the story of scandals, it 
now seemed to him, linked together tail to trunk like circus 
elephants. Every systemic market injustice arose from some 
loophole in a regulation created to correct some prior injustice. 
“No matter what the regulators did, some other intermedi- 
ary found a way to react, so there would be another form of 
front-running,” he said. When he was done in the Staten Island 
library he returned to work, as if there was nothing unusual 
at all about the product manager having turned himself into a 
private eye. He’d learned several important things, he told his 
colleagues. First, there was nothing new about the behavior they 
were at war with: The U.S. financial markets had always been 
either corrupt or about to be corrupted. Second, there was zero 
chance that the problem would be solved by financial regula- 
tors; or, rather, the regulators might solve the narrow problem 
of front-running in the stock market by high-frequency traders, 
but whatever they did to solve the problem would create yet 
another opportunity for financial intermediaries to make money 
at the expense of investors. 

Schwall’s final point was more aspiration than insight. For 



the first time in Wall Street history, the technology existed that 
eliminated entirely the need for financial intermediaries. Buyers 
and sellers in the U.S. stock market were now able to connect 
with each other without any need of a third party. “The way 
that the technology had evolved gave me the conviction that 
we had a unique opportunity to solve the problem,” he said. 
“There was no longer any need for any human intervention.” If 
they were going to somehow eliminate the Wall Street middle- 
men who had flourished for centuries, they needed to enlarge 
the frame of the picture they were creating. “I was so concerned 
that we were talking about what we were doing as a solution to 
high-frequency trading,” he said. “It was bigger than that. The 
goal had to be to eliminate any unnecessary intermediation.” 

BRAD FOUND IT odd that his product manager had set off to inves- 
tigate the history of Wall Street scandal — it was a bit like an 
offensive lineman choosing to skip practice to infiltrate the 
opposing team’s locker room. But Schwab’s side career as a pri- 
vate eye, at least at first, struck him as a harmless digression, of a 
piece with Schwab’s tendency in meetings to go oft' on tangents. 
“Once he gets on one of these bents it’s better just to let him go,” 
said Brad. “That’s just him working eighteen-hour days instead 
of fourteen-hour days.” 

Besides, they now had far bigger problems. By the middle of 
2011, Thor’s limitations were visible. “We had this meteoric rise 
in our business the first year and then it flatlines,” said Brad. In 
an open market, when customers were offered a new and bet- 
ter product, they ditched their old product for it. Wall Street 
banks weren’t subject to the usual open market forces. Inves- 
tors paid Wall Street banks for all sorts of reasons: for research. 



to keep them sweet, to get private access to corporate execu- 
tives, or simply because they had always done so. The way that 
they paid them was to give them their trades to execute — that 
is, they believed they needed to allocate some very large per- 
centage of their trades to the big Wall Street banks simply to 
maintain existing relations with them. RBC’s clients were now 
routinely calling to say, “Hey, we love using Thor, but there is 
only so much business we can do with you because we have to 
pay Goldman Sachs and Morgan Stanley.” 

The Royal Bank of Canada was running away with the title of 
Wall Street’s most popular broker by peddling a tool whose only 
purpose was to protect investors from the rest of Wall Street. 
The investors refused to draw the obvious conclusion that they 
should have a lot less to do with the rest of Wall Street. RBC 
had become the number-one-rated stockbroker in America and 
yet was still only the ninth best paid: They would never attract 
more than a tiny fraction of America’s stock market trades, and 
that fraction would never be enough to change the system. A 
guy Ronan knew at the big high-frequency trading shop Citadel 
called him one day and put the matter in a nutshell: I know what 
you’re doing. It’s genius. And there’s nothing we can do about it. But 
you are only two percent of the market. 

On top of that, the big Wall Street banks, seeing RBC’s suc- 
cess, were seeking to undermine it or at least to pretend to rep- 
licate it. “The tech people at other firms are calling me and 
saying, ‘I want to do Thor. How does Thor work?’ ” recalled 
Allen Zhang. The business people at the banks were now call- 
ing Ronan and Rob and offering them multiples of what they 
earned at RBC to leave. The whole of Wall Street had been in 
something like a two-year hiring freeze, and yet these big banks 
were suggesting to Ronan — who had spent the past fifteen years 



unable to get his foot in the door of any bank — that they’d pay 
him as much as $1.5 million to join them. Headhunters called 
Brad and told him that, if he was willing to leave RBC for a 
competitor, the opening bid was $3 million a year, guaranteed. 
Just to keep his team in place, Brad arranged for RBC to create a 
pool of money and set it aside: If the guys hung around for three 
years, they would be handed the money and would wind up 
being paid something closer to their market value. RBC agreed 
to do it, probably because Brad did not ask for a piece of the 
action himself and continued to work for far less than he could 
have made elsewhere. 

The bank’s marketing department proposed to Brad, as a way 
to get some media attention for Thor, that he apply for a Wall 
Street Journal Technology Innovation Award. Brad had never 
heard of the Wall Street Journal’s Technology Innovation Awards, 
but he thought that he might use the Wall Street Journal to tell 
the world just how corrupt the U.S. stock market had become. 
His bosses at RBC, when they got wind of his plans, wanted 
him to attend a lot of meetings — to discuss what he might say 
to the Wall Street Journal. They worried about their relationships 
with other Wall Street banks and with the public exchanges. 
“They didn’t want to ruffle anyone’s feathers,” says Brad. “There 
was not a lot I couldn’t say in a small closed forum, but they 
didn’t want me saying it openly.” He soon realized that, while 
RBC would allow him to apply for awards, it would not let 
him describe publicly what Thor had inadvertently exposed: the 
manner in which HFT firms front-ran ordinary investors; the 
conflict of interest that brokers had when they were being paid 
by the exchanges to route orders; the conflict of interest the 
exchanges had when they were being paid a billion dollars a year 
by HFT firms for faster access to market data; the implications of 



an exchange paying brokers to “take” liquidity; that Wall Street 
had found a way to bill investors without showing them the bill. 
“I had about eight things I wanted to say to the Journal ,” said 
Brad. “By the time I got through all these meetings, there was 
nothing to say. I was only allowed to say one of them — that we 
had found a way to route orders so they arrived at the exchanges 

That was the problem with being RBC nice: It rendered you 
incapable of going to war with nasty. Before Brad said any- 
thing at all to the Wall Street Journal, RBC’s upper management 
felt they needed to inform the U.S. regulators of what little he 
planned to say. They asked Brad to prepare a report on Thor 
for the SEC and then flew themselves down from Canada to 
join him in a big meeting with the SEC’s Division of Trad- 
ing and Markets staff. “It was more about not wanting them to 
be embarrassed about not knowing about Thor than it was us 
thinking they were going to do something about it,” Brad said. 
He had no idea what a meeting at the SEC was supposed to be 
like and prepared as if he were testifying before Congress. As 
he read straight from the document he had written, the people 
around the table listened, stoned-faced. “I was scared shitless,” 
he said. When he was finished, an SEC staffer said, What you are 
doing is not fair to high-frequency traders. You’re not letting them get out 
of the way. 

Excuse me? said Brad. 

The SEC staffer argued that it was unfair that high-frequency 
traders couldn’t post phony bids and offers on the exchanges to 
extract information from actual investors without running the 
risk of having to stand by them. It was unfair that Thor forced 
them to honor the markets they claimed to be making. Brad just 
looked at the guy: He was a young Indian quant. 



Then a second staffer, a much older guy, raised his hand and 
said, If they don’t want to be on the offer they shouldn’t be there at all. 

A lively argument ensued, with the younger SEC staffers tak- 
ing the side of high-frequency trading and the older half tak- 
ing Brad’s point. “There was no clear consensus,” said Brad. 
“But it gave me a sense that they weren’t going to be doing 
anything anytime soon.”* After the meeting, RBC conducted 
a study, never released publicly, in which they found that more 
than two hundred SEC staffers since 2007 had left their govern- 
ment jobs to work for high-frequency trading firms or the firms 
that lobbied Washington on their behalf. Some of these people 
had played central roles in deciding how, or even whether, to 
regulate high-frequency trading. For instance, in June 2010, the 
associate director of the SEC’s Division of Trading and Markets, 
Elizabeth King, had quit the SEC to work for Getco. The SEC, 
like the public stock exchanges, had a kind of equity stake in the 
future revenues of high-frequency traders. 

The argument in favor of high-frequency traders had beaten 
the argument against them to the U.S. regulators. It ran as fol- 
lows: Natural investors in stocks, the people who supply capi- 
tal to companies, can’t find each other. The buyers and sellers 
of any given stock don’t show up in the market at the same 
time, so they needed an intermediary to bridge the gap, to buy 
from the seller and to sell to the buyer. The fully computerized 
market moved too fast for a human to intercede in it, and so 
the high-frequency traders had stepped in to do the job. Their 

* “There’s a culture in the SEC of not getting into a dialogue with any individual who 
comes in,” says a staffer who listened to Brad Katsuyama’s presentation. “They don’t 
want to give any one person an unfair peek at the way the SEC thinks. But it’s a very 
defensive culture. And there were people in the room who had written some of the rules 
he was implicitly criticizing.” 



importance could be inferred from their activity: In 2005 a 
quarter of all trades in the public stock markets were made 
by HFT firms; by 2008 that number had risen to 65 percent. 
Their new market dominance — so the argument went — was a 
sign of progress, not just necessary but good for investors. Back 
when human beings sat in the middle of the stock market, the 
spreads between the bids and the offers of any given stock were 
a sixteenth of a percentage point. Now that computers did the 
job, the spread, at least in the more actively traded stocks, was 
typically a penny, or one-hundredth of 1 percent. That, said the 
supporters of high-frequency trading, was evidence that more 
HFT meant more liquidity. 

The arguments against the high-frequency traders hadn’t 
spread nearly so quickly — at any rate, Brad didn’t hear them 
from the SEC. A distinction cried out to be made, between 
“trading activity” and “liquidity.” A new trader could leap into a 
market and trade frantically inside it without adding anything of 
value to it. Imagine, for instance, that someone passed a rule, in 
the U.S. stock market as it is currently configured, that required 
every stock market trade to be front-run by a firm called Scalp- 
ers Inc. Under this rule, each time you went to buy 1,000 shares 
of Microsoft, Scalpers Inc. would be informed, whereupon it 
would set off to buy 1,000 shares of Microsoft offered in the 
market and, without taking the risk of owning the stock for 
even an instant, sell it to you at a higher price. Scalpers Inc. is 
prohibited from taking the slightest market risk; when it buys, 
it has the seller firmly in hand; when it sells, it has the buyer in 
hand; and at the end of every trading day, it will have no posi- 
tion at all in the stock market. Scalpers Inc. trades for the sole 
purpose of interfering with trading that would have happened 
without it. In buying from every seller and selling to every 



buyer, it winds up: a) doubling the trades in the marketplace 
and b) being exactly 50 percent of that booming volume. It adds 
nothing to the market but at the same time might be mistaken 
for the central player in that market. 

This state of affairs, as it happens, resembles the United States 
stock market after the passage of Reg NMS. From 2006 to 
2008, high-frequency traders’ share of total U.S. stock mar- 
ket trading doubled, from 26 percent to 52 percent — and it has 
never fallen below 50 percent since then. The total number of 
trades made in the stock market also spiked dramatically, from 
roughly 10 million per day in 2006 to just over 20 million per 
day in 2009. 

“Liquidity” was one of those words Wall Street people threw 
around when they wanted the conversation to end, and for 
brains to go dead, and for all questioning to cease. A lot of 
people used it as a synonym for “activity” or “volume of trad- 
ing,” but it obviously needed to mean more than that, as activ- 
ity could be manufactured in a market simply by adding more 
front-runners to it. To get at a useful understanding of liquidity 
and the likely effects of high-frequency trading on it, one might 
better begin by studying the effect on investors’ willingness to 
trade once they sense that they are being front-run by this new 
front-running entity. Brad himself had felt the effect: When the 
market as displayed on his screens became illusory, he became 
less willing to take risk in that market — to provide liquidity. He 
could only assume that every other risk-taking intermediary — 
every other useful market participant — must have felt exactly 
the same way. 

The argument for HFT was that it provided liquidity, but 
what did this mean? “HFT firms go home flat every night,” said 
Brad. “They don’t take positions. They are bridging an amount 



of time between buyers and sellers that’s so small that no one 
even knows it exists.” After the market was computerized and 
decimalized, in 2000, spreads in the market had narrowed — that 
much was true. Part of that narrowing would have happened 
anyway, with the automation of the stock market, which made 
it easier to trade stocks priced in decimals rather than in frac- 
tions. Part of that narrowing was an illusion: What appeared to 
be the spread was not actually the spread. The minute you went 
to buy or sell at the stated market price, the price moved. What 
Scalpers Inc. did was to hide an entirely new sort of activity 
behind the mask of an old mental model — in which the guy 
who “makes markets” is necessarily taking market risk and pro- 
viding “liquidity.” But Scalpers Inc. took no market risk.* 

In spirit Scalpers Inc. was less a market enabler than a weird 
sort of market burden. Financial intermediation is a tax on capi- 
tal; it’s the toll paid by both the people who have it and the 
people who put it to productive use. Reduce the tax and the 
rest of the economy benefits. Technology should have led to a 
reduction in this tax; the ability of investors to find each other 
without the help of some human broker might have eliminated 
the tax altogether. Instead this new beast rose up in the middle 
of the market and the tax increased — by billions of dollars. Or 
had it? To measure the cost to the economy of Scalpers Inc., you 
needed to know how much money it made. That was not pos- 
sible. The new intermediaries were too good at keeping their 

* In early 2013, one of the largest high-frequency traders, Virtu Financial, publicly 
boasted that in five and a half years of trading it had experienced just one day when 
it hadn’t made money, and that the loss was caused by “human error.” In 2008, Dave 
Cummings, the CEO of a high-frequency trading firm called Tradebot, told university 
students that his firm had gone four years without a single day of trading losses. This sort 
of performance is possible only if you have a huge informational advantage. 



profits secret * Secrecy might have been the signature trait of the 
entities who now sat at the middle of the stock market: You had 
to guess what they were making from what they spent to make 
it. Investors who eyeballed the situation did not find reason for 
hope. “There used to be this guy called Vinny who worked on 
the floor of the stock exchange,” said one big investor who had 
observed the market for a long time. “After the markets closed 
Vinny would get into his Cadillac and drive out to his big house 
in Long Island. Now there is the guy called Vladimir who gets 
into his jet and flies to his estate in Aspen for the weekend. I 
used to worry a little about Vinny. Now I worry a lot about 

Apart from taking some large sum of money out of the market, 
and without taking risk or adding anything of use to that mar- 
ket, Scalpers Inc. had other, less intended consequences. Scalpers 
Inc. inserted itself into the middle of the stock market not just as 
an unnecessary middleman but as a middleman with incentives 
to introduce dysfunction into the stock market. Scalpers Inc. 
was incentivized, for instance, to make the market as volatile 
as possible. The value of its ability to buy Microsoft from you 
at $30 a share and to hold the shares for a few microseconds — 
knowing that, even it the Microsoft share price began to fall, it 
could turn around and sell the shares at $30.01 — was determined 
by how likely it was that Microsoft’s share price, in those magi- 
cal microseconds, would rise in price. The more volatile Micro- 
soft’s share price, the higher Microsoft’s stock price might move 

* A former employee of Citadel who also once had top secret security clearance at the 
Pentagon says, “To get into the Pentagon and into my area, it took two badge swipes. 
One to get into the building and one to get into my area. Guess how many badge swipes 
it took me to get to my seat at Citadel? Five.” 



during those microseconds, and the more Scalpers Inc. would be 
able to scalp. One might argue that intermediaries have always 
profited from market volatility, but that is not really true. The 
old specialists on the New York Stock exchange, for instance, 
because they were somewhat obliged to buy in a falling market 
and to sell in a rising one, often found that their worst days were 
the most volatile days. They thrived in times of relative stability. 

Another incentive of Scalpers Inc. is to fragment the market- 
place: The more sites at which the same stocks changed hands, 
the more opportunities to front-run investors from one site to 
another. The bosses at Scalpers Inc. would thus encourage new 
exchanges to open, and would also encourage them to place 
themselves at some distance from each other. Scalpers Inc. also 
had a very clear desire to maximize the difference between the 
speed of their private view of the market and the view afforded 
the wider public market. The more time that Scalpers Inc. 
could sit with some investor’s stock market order, the greater 
the chance that the price might move in the interim. Thus an 
earnest employee of Scalpers Inc. would look for ways either to 
slow down the public’s information or to speed up his own. 

The final new incentive introduced by Scalpers Inc. was per- 
haps the most bizarre. The easiest way for Scalpers Inc. to extract 
the information it needed to front-run other investors was to 
trade with them. At times it was possible to extract the necessary 
information without having to commit to a trade. That’s what 
the “flash order” scandal had been about: high-frequency trad- 
ers being allowed by the exchanges to see other people’s orders 
before anyone else, without any obligation to trade against them. 
But for the most part, if you wanted to find out what some big 
investor was about to do, you needed to do a little bit of it with 
him. For instance, to find out that, say, T. Rowe Price wanted 



to buy 5 million shares of Google Inc., you needed to sell some 
Google to T. Rowe Price. That initial market contact between 
any investor and Scalpers Inc. was like the bait in a trap — a loss 
leader. For Scalpers Inc., the goal was to spend as little as pos- 
sible to acquire the necessary information — to make those initial 
trades, the bait, as small as possible. 

To an astonishing degree, since the implementation of Reg 
NMS, the U.S. financial markets had evolved to serve the nar- 
row interests of Scalpers Inc. Since the mid-2000s, the average 
trade size in the U.S. stock market had plummeted, the markets 
had fragmented, and the gap in time between the public view 
of the markets and the view of high-frequency traders had wid- 
ened. The rise of high-frequency trading had been accompanied 
also by a rise in stock market volatility — over and above the 
turmoil caused by the 2008 financial crisis. The price volatil- 
ity within each trading day in the U.S. stock market between 
2010 and 2013 was nearly 40 percent higher than the volatility 
between 2004 and 2006, for instance. There were days in 2011 
in which volatility was higher than in the most volatile days of 
the dot-com bubble. 

The financial crisis brought with it a great deal of stock mar- 
ket volatility; perhaps people just assumed that there was sup- 
posed to be an unusual amount of drama in the stock market 
evermore. But then the financial crisis abated and the drama 
remained. There was no good explanation for this, but Brad 
now had a glimmer of one. It had to do with the way a front- 
runner operates. A front-runner sells you a hundred shares of 
some stock to discover that you are a buyer and then turns around 
and buys everything else in sight, causing the stock to pop higher 
(or the opposite, if you happen to be a seller). The Royal Bank of 
Canada had tested the effects on stock market volatility of using 



Thor, which stymied front-runners, rather than the standard 
order routers used by Wall Street, which did not. The sequential 
cost-effective router responded to the kickbacks and fees of the 
various exchanges and went to those exchanges first that paid 
them the most to do so. The spray router — which, as its name 
suggests, just sprayed the market and took whatever stock was 
available, or tried to — did not make any effort to compel a stock 
market order to arrive at the different exchanges simultaneously. 
Every router, when it bought stock, tended to drive the price 
of that stock a bit higher. But when the stock had settled — say, 
ten seconds later — it settled differently with each router. The 
sequential cost-effective router caused the share price to remain 
higher than the spray router did, and the spray router caused it to 
move higher than Thor did. “I have no scientific evidence,” said 
Brad. “This is purely a theory. But with Thor the HFT firms are 
trying to cover their losses. I’m short when I don’t want to be, so I 
need to buy to cover, quickly.” The other two routers enabled HFT 
to front-run, so they wound up being long the stock. “[With] 
the other two, HFT is in a position to trade around a winning 
position,” said Brad, “and they can do whatever they can do 
to force the stock even higher.” (Or lower, if the investor who 
triggered the activity is a seller.) They had, in those privileged 
microseconds, the reckless abandon of gamblers playing with 
house money. 

The new choppiness in the public U.S. stock markets was 
spreading to other financial markets, as they, too, embraced 
high-frequency traders. It was what investors most noticed: 
They were less and less able to buy and sell big chunks of stock 
in a gulp. Their frustration with the public stock exchanges had 
led the big Wall Street banks to create private exchanges: dark 
pools. By the middle of 2011, roughly 30 percent of all stock 



market trades occurred off the public exchanges, most of them 
in dark pools. The appeal of these dark pools — said the Wall 
Street banks — was that investors could expose their big stock 
market orders without fear that those orders would be exploited. 

WHAT BOTHERED RICH Gates, at least at first, was the tone of 
the pitch he was hearing from the big Wall Street banks. All 
through 2008 and 2009 they would come to his office and tell 
him why he needed their algorithms to defend himself in the 
stock market. This algo is like a tiger that lurks in the woods and waits 
for the prey and then jumps on it. Or: This algo is like an anaconda 
in a tree. The algos had names like Ambush and Nighthawk and 
Raider and Dark Attack and Sumo. Citi had one called Dagger, 
Deutsche Bank had Sheer, and Credit Suisse had one named 
Guerrilla, which came, in the bank’s flip-chart presentation, 
with a menacing drawing of Che Guevara wearing a beret and 
scowling. What the hell was that about? Their very names made 
Rich Gates wary; he also didn’t like how loudly the brokers 
selling them told him they’d come to protect him. Protect him 
from what? Why did he need protection? From whom did he 
need to be protected? “I’m immediately skeptical of people say- 
ing they are looking out for my interests,” Gates said. “Espe- 
cially on Wall Street.” 

Gates ran a mutual fund, TFS Capital, that he had created in 
1997 with friends from the University of Virginia. Fie liked to 
think of himself as a hick, but in truth he was a keenly analytical 
math geek in the perfectly pleasant Philadelphia suburb of West 
Chester. He managed nearly $2 billion belonging to 35,000 
small investors but still positioned himself, even in his own 
mind, as an industry outsider. He believed that mutual funds 



were less often exercises in smart money management than in 
creepy marketing, and that many of the people who ran mutual 
funds should be doing something else with their lives. Back in 
2007, to make this point, he dug out of a stack of league tables 
America’s worst-performing mutual fund: the Phoenix Market 
Neutral Fund. Over the prior decade, Gates’s firm had earned its 
investors returns of 10 percent per year. Over that same period, 
the Phoenix Market Neutral Fund had lost .09 percent a year for 
its investors — the investors would have been better oft hopping 
over the fence of the president of the Phoenix Market Neu- 
tral Fund’s home and burying the money in his backyard. Gates 
wrote a letter to the Phoenix president saying, in effect, You are 
so obviously inept at managing money that you could do your investors 
a favor by turning over all of your assets to me and letting me run them 
for you. The president failed to reply. 

The machismo of Wall Street’s algorithms, combined with 
what struck Gates as a lot of nonsensical talk about the need 
for trading speed, stirred his naturally suspicious mind. “I just 
noticed a lot of bullshit,” he said. He and his colleagues devised a 
test to see if there was anything in this new stock market to fear. 
The test, specifically, would show him if, when he entered an 
order into one of Wall Street’s dark pools, he wound up getting 
ripped off by some unseen predator. He started by identifying 
stocks that didn’t trade very often. Chipotle Mexican Grill, for 
instance. He sent in an order to a single Wall Street dark pool 
to buy that stock at the “mid-market” price. Say, for example, 
that the shares of Chipotle Mexican Grill were trading at 100— 
100.10. Gates would submit his bid to buy a thousand shares of 
Chipotle at $100.05. There it would normally just sit until some 
other investor came along and lowered his price from $100.10 to 
$100.05. Gates didn’t wait for that to happen. Instead, a few sec- 



onds later, he sent a second order to one of the public exchanges, 
to sell Chipotle at $100.01. 

What should have happened next was that his order in the 
dark pool should have been fdled at $100.01, the official new best 
price in the market. He should have been able to buy from him- 
self the shares he was selling at $100.01. But that’s not what hap- 
pened. Instead, before he could blink his eye, he had made two 
trades. He had bought Chipotle from someone inside the Wall 
Street dark pool at $100.05 and sold it to someone else on the 
public exchange for $100.01. He’d lost 4 cents by, in effect, trad- 
ing with himself. Only he hadn’t traded with himself; some third 
party had obviously used the sell order he had sent to the public 
exchange to exploit the buy order he had sent to the dark pool. 

Gates and his colleagues wound up making hundreds of such 
tests, with their own money, in several Wall Street dark pools. 
In the first half of 2010 there was only one Wall Street firm in 
whose dark pool the test came back positive: Goldman Sachs. In 
the Goldman dark pool, Sigma X, he got ripped off a bit more 
than half the time he ran the test. As Gates traded in lightly 
traded stocks, and high-frequency trading firms were over- 
whelmingly interested in heavily traded ones, these tests would 
have been vastly more likely to generate false negatives than false 
positives. Still, he was a bit surprised that Goldman, and only 
Goldman, seemed to be running a pool that allowed someone 
else to front-run his orders to the public stock exchanges. He 
called his broker at Goldman. “He said it wasn’t fair,” said Gates, 
“because it wasn’t just them. He said, ‘It’s happening all over. It’s 
not just us.’ ” 

Gates was dutifully shocked. “When I first saw the results of 
these tests, I thought: This obviously is not right. As far as he 
could tell, no one seemed much to care that 35,000 small inves- 



tors could be so exposed to predation inside Wall Street’s most 
prominent bank. “I’m amazed that people don’t ask the ques- 
tions,” he said. “That they don’t dig deeper. If some schmuck 
in West Chester, PA, can figure it out, I’ve got to believe other 
people did, too.” Outraged, Gates called a reporter he knew 
at the Wall Street Journal. The reporter came to see Gates’s tests 
and seemed interested, but two months later there was still no 
piece in the Journal — and Gates sensed that there might never 
be. (Among other things, the reporter was uncomfortable men- 
tioning Goldman Sachs by name.) At which point Gates noticed 
that the Dodd-Frank Wall Street Reform and Customer Pro- 
tection Act, soon to be passed, contained a whistle-blower pro- 
vision. “I’m like, ‘Holy crap, I’m trying to out this anyway. If I 
can get paid, too — great.’ ” 

The people who worked in the SEC’s Division of Trading 
and Markets were actually great — nothing like what the pub- 
lic imagined. They were smart and asked good questions and 
even spotted small mistakes in Gates’s presentation, which he 
appreciated — though, as with Brad Katsuyama, they gave him 
no idea how they might respond to the information he’d given 
them. They wondered, shrewdly, exactly who was ripping off 
investors in Goldman’s dark pool. “They wanted to know if 
Goldman Sachs’s prop group was on the other side of the trade,” 
said Gates. He had no answer for that. “They don’t tell you who 
took the other side of the trade,” he said. All he knew was that 
he’d been ripped off, in exactly the way you might expect to be 
ripped off, when you can’t see the market trading in real time 
and others can. 

And that, at least for a few months, was that. “After I blew the 
whistle, I laid low,” Gates said. “I just wanted to focus on our 
business. I don’t get off throwing bombs.” Then came the flash 



crash, and the Wall Street Journal’s interest was rekindled. The 
paper published a piece on Rich Gates’s tests — without men- 
tioning Goldman Sachs by name. “I think it’s going to set the 
world on fire,” said Gates. “It didn’t do anything. There are fif- 
teen comments at the bottom of the piece on the Web, and all of 
them are Russian mail order brides.” But the piece led a person 
close to both the BATS exchange and Credit Suisse to get in 
touch with Gates with a suggestion: Run your tests again, spe- 
cifically on the BATS exchange and the Credit Suisse dark pool 
called Crossfinder. Just to see. Toward the end of 2010, Gates ran 
another round of tests. 

Sure enough, he was able to get himself ripped off, in exactly 
the same way he had been ripped off in the Goldman Sachs 
dark pool — on the BATS exchange, and inside the Credit Suisse 
dark pool, and in some other places, too. At Goldman Sachs, 
however, the tests were now negative. “When we did it the 
first time,” he said, “it worked at Goldman but nowhere else. 
When we did it six months later it didn’t work at Goldman, but 
it worked everywhere else.” 

IN MAY 2011, the small team Brad had created — Schwall, Ronan, 
Rob Park, a couple of others — sat around a table in Brad’s office, 
surrounded by the applications of past winners of the Wall Street 
Journal’s Technology Innovation Awards. As it turned out, 
RBC’s marketing department had informed them of the awards 
the day before submissions were due — so they were scrambling 
to figure out in which of several categories they belonged, and 
how to make Thor sound life-changing. “There were papers 
everywhere,” said Rob. “No one sounded like us. There were 
people who had, like, cured cancer.” “It was stupid,” said Brad, 



“there wasn’t even a category to put us into. I think we ended 
up applying under Other .” 

With the purposelessness of the exercise hanging in the air, 
Rob said, “I just had a sick idea.” Rob’s idea was to license the 
technology to one of the exchanges. (Schwall had patented Thor 
for RBC.) The line between Wall Street brokers and exchanges 
had blurred. The big Wall Street banks now ran their own pri- 
vate exchanges. The stock exchanges, for their part, were making 
a bid to become brokers. The bigger ones now offered a service 
that enabled brokers to simply hand them their stock market 
orders, which they would then route. To their own exchange, of 
course, but also to others. The service was used mainly by small 
regional brokerage firms that didn’t have their own routers, but 
this brokerage-like service opened up, at least in Rob’s mind, a 
new possibility. If just one of the exchanges was handed the tool 
for protecting investors from market predators, the small brokers 
from around the country might flock to it, and it might become 
the mother of all exchanges. 

“Screw that,” said Brad. “Let’s just create our own stock 

“We just sat there for a while,” said Rob. “Kind of staring at 
each other. Create your oum stock exchange. What does that even 

A few weeks later Brad flew to Canada and sold his bosses 
on the idea of an RBC-led stock exchange. Then, in the fall of 
2011, he canvassed a handful of the world’s biggest money man- 
agers (Janus Capital, T. Rowe Price, BlackRock, Wellington, 
Southeastern Asset Management) and some of its most influen- 
tial hedge fund managers (David Einhorn, Bill Ackman, Daniel 
Loeb). They all had the same reaction. They loved the idea of a 
stock exchange that protected investors from Wall Street’s pred- 



ators. They also thought that a new stock exchange, to be cred- 
ibly independent of Wall Street, could not be created by a Wall 
Street bank. Not even a bank as nice as RBC. If Brad wanted to 
create the mother of all stock exchanges, he would need to quit 
his job and do it on his own. 

The challenges were obvious. He’d need to find money. He’d 
need to persuade a lot of highly paid people to quit their Wall 
Street jobs to work for tiny fractions of their current salaries — 
and possibly even supply the capital to pay themselves to work. 
“I was asking: Can I get the people I need? How long can we 
survive without getting paid? Will our significant others let us 
do this?” He also needed to find out if the nine big Wall Street 
banks that controlled nearly 70 percent of all stock market orders* 
would be willing to send those orders to a truly safe exchange. 
It would be far more difficult to start an exchange premised on 
fairness if the banks that controlled the vast majority of the cus- 
tomers’ orders were committed to unfairness. 

For a surprisingly long time, Brad had reserved final judg- 
ment about the biggest Wall Street banks. “I held out a degree 
of hope that the people at [each] bank who handled the clients’ 
orders were removed from the prop group,” he said. His hope 
sprang mainly from his own experience: At RBC, where he 
handled the clients’ orders, he barely knew the prop traders and 
had no idea what they were doing. There was a reason for this: 
RBC had not created a dark pool, because Brad had killed the 
idea. Still, he knew that each of the big Wall Street banks had its 
own internal politics, and that there were people in each of them 

* Those nine banks, in order of their (fairly evenly distributed) 2011 market share, from 
highest to lowest: Credit Suisse, Morgan Stanley, Bank of America, Merrill Lynch, 
Goldman Sachs, J.P. Morgan, Barclays, UBS, Citi, Deutsche Bank. 



who wanted to act in the long-term interests of their firms and 
do the right thing by their customers. His hope was that some of 
these people, in some of these places, had power. 

John Schwall’s private investigations put an end to that hope. 
By the fall of 2011 Schwab had become something like a con- 
noisseur of the uses of Linkedln to find stuff out about people 
in and around high-frequency trading. He’d put a face on high- 
frequency trading, or rather two faces. “I began to anticipate 
that certain people were in on the game,” said Schwab. “I’d 
connect to them so that I could see their network. There were 
maybe twenty-five guys I called kingpins — the people who 
actually knew what was going on.” At the very top of the food 
chain were a lot of white guys in their forties whose careers 
could be traced back, one way or another, to the early elec- 
tronic stock exchanges born of the regulations passed after the 
crash of 1987 — Wall Street guys who might have some techni- 
cal background but whose identity was more trader than pro- 
gramming geek. 

The new players in the financial markets, the kingpins of the 
future who had the capacity to reshape those markets, were a 
different breed: the Chinese guy who had spent the previous 
ten years in American universities; the French particle physicist 
from FERMAT lab; the Russian aerospace engineer; the Indian 
PhD in electrical engineering. “There were just thousands of 
these people,” said Schwab. “Basically all of them with advanced 
degrees. I remember thinking to myself how unfortunate it was 
that so many engineers were joining these firms to exploit inves- 
tors rather than solving public problems.” These highly trained 
scientists and technicians tended to be pulled onto Wall Street by 
the big banks and then, after they’d learned the ropes, to move 
on to smaller high-frequency trading shops. They behaved more 



like free agents than employees of a big corporation. In their 
Linkedln profiles, for instance, they revealed all sorts of infor- 
mation that their employers almost certainly would not want 
revealed. Here Schwall stumbled upon the predator’s weakness: 
The employees of the big Wall Street banks felt no more loyalty 
toward the banks than the banks felt toward them. 

The employees of Credit Suisse offered the clearest exam- 
ple. Credit Suisse’s dark pool, Crossfmder, vied with Gold- 
man Sachs’s Sigma X to be Wall Street’s biggest private stock 
exchange. Credit Suisse’s biggest selling point to investors was 
that it put their interests first and protected them from whatever 
it was that high-frequency traders were doing. Back in October 
2009, the head of Advanced Execution Services (AES) at Credit 
Suisse, Dan Mathisson, had testified before a U.S. Senate Bank- 
ing, Housing, and Urban Affairs Committee at a hearing on 
dark pools. “The argument that dark pools are somehow part of 
the high-frequency trading debate simply does not make sense,” 
he’d said. “High-frequency traders make their money by digest- 
ing publicly available information faster than others; dark pools 
hide order information from everyone.” 

That, Schwall thought, because Brad had explained it all to 
him, was simply wrong. It was true that when, say, a pension fund 
gave a Wall Street bank an order to buy 100,000 shares of Micro- 
soft, and the Wall Street bank routed the order to the dark pool, 
the wider world was not informed. But that was just the begin- 
ning of the story. The pension fund did not know the rules of 
the dark pool, and could not see how the buy order was handled 
inside of it. The pension fund would not be able to say, for exam- 
ple, whether the Wall Street bank allowed its own proprietary 
traders to know of the big buy order, or if those traders had used 
their (faster than the dark pool) market connections to front-run 



the order on the public exchanges. Even if the Wall Street bank 
resisted the temptation to trade for itself against its own custom- 
ers, there was virtually no chance they resisted the temptation to 
sell access to the dark pool to high-frequency traders. The Wall 
Street banks did not disclose which high-speed trading firms had 
paid them for special access to their dark pools, or how much they 
had paid, but selling that access was standard practice. 

Raising, again, the obvious question: Why would anyone pay 
for access to the customers’ orders inside a Wall Street bank’s dark 
pool? The straight answer was that a customer’s stock market 
order, inside a dark pool, was fat and juicy prey. The order was 
typically large, and its movements were especially predictable: 
Each Wall Street bank had its own detectable pattern for han- 
dling orders. The order was also slow, because of the time it 
was forced to spend inside the dark pool before accessing the 
wider market. As Brad had put it, “You could front-run an 
order in a dark pool on a bicycle.” The pension fund trying to 
buy 100,000 shares of Microsoft could, of course, specify that 
the Wall Street bank not take its orders to the public exchanges 
at all but simply rest it, hidden, inside the dark pool. But an 
order hidden inside a dark pool wasn’t very well hidden. Any 
decent high-frequency trader who had paid for a special con- 
nection to the pool would ping the pool with tiny buy and sell 
orders in every listed stock, searching for activity. Once they’d 
discovered the buyer of Microsoft, they’d simply wait for the 
moment when Microsoft ticked lower on the public exchanges 
and sell it to the pension fund in the dark pool at the stale, 
higher “best” price (as Rich Gates’s tests had demonstrated). 
It was riskless, larcenous, and legal — made so by Reg NMS. 
The way Brad had described it, it was as if only one gambler 
were permitted to know the scores of last week’s NFL games, 



with no one else aware of his knowledge. He places bets in the 
casino on every game and waits for other gamblers to take the 
other side of those bets. There’s no guarantee that anyone will 
do so; but if they do, he’s certain to win. 

In his investigation of the people who managed Credit Suisse’s 
dark pool, one of the first things Schwab noticed was the guy 
in charge of electronic trading: Josh Stampfli, who had joined 
Credit Suisse after seven years spent working for Bernie Madoff. 
(Madoff had pioneered the idea of paying brokers for the right to 
execute the brokers’ customers’ orders, which should have told 
people something but apparently did not.) This, of course, only 
heightened Schwab’s suspicions, and sent him digging around 
in old articles in trade journals about Credit Suisse’s dark pool.* 
There he found references and allusions that made sense only 
if Credit Suisse had planned, right from the start, to be deeply 
involved with high-frequency trading firms. For instance, in 
April 2008 a guy named Dmitri Galinov, a director and the 
head of liquidity strategy at Credit Suisse, had told the Securi- 
ties Technology Monitor that many of Credit Suisse’s “clients” had 
placed computer servers in Weehawken, New Jersey, to be closer 
to Credit Suisse’s dark pool. The only people who put servers 
next to dark pools in Weehawken were Ronan’s old clients — the 
high-frequency trading firms. No stock market investor went to 
such lengths to shave microseconds off trading time. 

“Client,” to Credit Suisse, appeared to Schwab to be a cat- 
egory that included “high-frequency trading firms.” Schwab’s 
suspicion that Credit Suisse wanted to service HFT while not 
seeming to do so grew after he read an interview Dan Mathisson 
gave to the New York Times in November 2009. 

* Stampfli has not been charged with any wrongdoing. 



Q: Who are your clients at CrossFinder [sic] and how do they 
benefit from using a dark pool as opposed to just going through 
a broker and trading on the exchange? 

A: Our clients are mutual funds, pension funds, hedge funds 
and some other large broker-dealers, so it is always institutional 
clients . . . 

All the large high-frequency trading firms, Schwall knew, 
were “broker-dealers.” They had to be, to gain the special access 
they had to the public stock exchanges. So Mathisson had not 
ruled out dealing with them. The only reason he would not 
explicitly rule out dealing with them, Schwall assumed, was that 
he was dealing with them. 

The Linkedln searches became a new obsession. The former 
MadofF employee’s profile led him to the people who worked for 
the former MadofF employee, who led him to the people who 
worked for them, and so on. Even as Credit Suisse tried to appear 
as if it had nothing to do with high-frequency trading, its employ- 
ees begged to differ. Schwall dug out dozens of examples of Credit 
Suisse’s computer programmers boasting on their resumes about 
“building high-frequency trading platforms” and “implementing 
high-frequency trading strategy,” or of experience as a “quan- 
titative trader on equity and equity derivatives: high-frequency 
trading.” One guy explained that he had “managed on-boarding 
of all high-frequency clients to Crossfinder.” Another said he had 
built the Credit Suisse Crossfinder dark pool and now worked in 
high-frequency trading market making. Credit Suisse claimed 
that its dark pool had nothing to do with high-frequency trad- 
ing, and yet it somehow employed, in and around its dark pool, a 
mother lode of high-frequency trading talent. 



By the time he’d finished, Schwall had built the entire Credit 
Suisse dark pool organization chart. “He’s got these people 
charts,” said Brad incredulously. “It’s like one of those FBI 
boards, with the drug kingpins.” Looking over Schwall’s charts 
on Credit Suisse, the bank that went to the most trouble to sell 
itself as safe to investors, Brad decided that the game was prob- 
ably over inside all the big Wall Street banks. All of them, one 
way or another, were probably using the unequal speeds in the 
market to claim their share of the prey. He further assumed that 
the big Wall Street banks must have stumbled upon his solution 
to high-frequency front-running, and must have chosen not to 
use it, because they had too great a stake in the profits generated 
by that front-running. “It became very obvious to me why we 
were the first to discover Thor, because we weren’t,” he said. 

What that meant to me was that the problem was going to 
be much, much harder to solve. It also told me why the clients 
were so in the dark, because the clients rely on brokers for infor- 
mation.” Creating an exchange designed to protect the prey 
from the predator would mean starting a war on Wall Street — 
between the banks and the investors they claimed to represent. 

Schwall’s private investigations also revealed to Brad just how 
little the technical people understood of their role in the financial 
world. “It’s not like you are building a bridge connecting two 
pieces of land,” he said. “You can’t see the effects of what you are 
doing.” The openness with which the Credit Suisse technolo- 
gists described their activities made him aware of a larger, almost 
charming obliviousness. “I was totally shocked when John started 
to pull out these resumes,” he recalled. “The banks had adopted 
a policy of saying as little as possible about what they were actu- 
ally doing. They’d fire people for being quoted in the newspaper, 
but in their Linkedln pages those same people said whatever they 



wanted.” From the way the engineers described their roles in the 
new financial system, he could see that they had no clue about 
the injustices of that system. “It told me that these tech guys were 
completely oblivious to what they were working on,” he said. 
“They were tying these things they were working on — helping 
the bank to make markets in their dark pools; building auto- 
mated systems for the bank to use with its customers — in a way 
you never would if you understood what the banks were doing. 
It’s like saying on your Linkedln profile, ‘I have all the skills of a 
robber and I know this one house intimately.’ ” 

Schwall had started out looking for the villains who were 
committing crimes against the life savings of ordinary Ameri- 
cans, fully aware of their own villainy. He wound up finding, 
mainly, a bunch of people who had no idea of the meaning 
of their own lives. In his searches, Schwall noticed something 
else, though at first he didn’t know what to make of it: A sur- 
prisingly large number of the people pulled in by the big Wall 
Street banks to build the technology for high-frequency trad- 
ing were Russians. “If you went to Linkedln and looked at one 
of these Russian guys, you would see he was linked to all the 
other Russians,” said Schwall. “I’d go to find Dmitri and I’d also 
find Misha and Vladimir and Tolstoy or whatever.” The Rus- 
sians came not from finance but from telecom, physics, medical 
research, university math departments, and a lot of other useful 
fields. The big Wall Street firms had become machines for turn- 
ing analytically minded Russians into high-frequency traders. 
Schwall filed that fact away for later, as something perhaps worth 
thinking about. 



S ergey Aleynikov wasn’t the world’s most eager immi- 
grant to America, or, for that matter, to Wall Street. He’d 
left Russia in 1990, the year after the fall of the Berlin 
Wall, but more in sadness than in hope. “When I was nineteen I 
haven’t imagined leaving it,” he says. “I was very patriotic about 
Russia. I cried when Brezhnev died. And I always hated English. 
I thought I was completely incapable of learning languages.” His 
problem with Russia was that its government wouldn’t allow 
him to study what he wanted to study. He wasn’t religious in any 
conventional sense, but he’d been born a Jew, which had been 
noted on his Russian passport to remind everyone of the fact. 
As a Jew he expected to be given especially difficult entrance 
exams to university, which, if he passed them, would grant him 
access to just one of two Moscow universities that were more 
accepting of Jews, where he would study whatever the authori- 
ties permitted Jews to study. Math, in Serge’s case. He’d been 
willing to tolerate this state of affairs; however, as it happened. 



he’d also been born to program computers. He hadn’t laid hands 
on a computer until 1986, when he was already sixteen. The 
first thing he’d done was to write a program: He instructed the 
computer to draw a picture of a sine wave. When the computer 
actually followed his instructions, he was hooked. What hooked 
him, he said, was “its detailed orientation. The way it requires 
an ability to see the problem and tackle it from different angles. 
It’s not just like chess, but like solving a particular problem in 
chess. The more challenging problem is not to play chess but 
to write the code that will play chess.” He found that coding 
engaged him not just intellectually but also emotionally. “Writ- 
ing a program is like giving birth to a child,” he said. “It is a 
creation. Even though it is technical, it is a work of art. You get 
this level of satisfaction.” 

He applied to switch his major from mathematics to computer 
science, but the authorities forbade it. “That is what tipped me 
to accept the idea that perhaps Russia is not the best place for 
me,” he says. “When they wouldn’t allow me to study computer 

He arrived in New York City in 1990 and moved into a 
dorm room at the 92nd Street Young Men’s and Young Wom- 
en’s Hebrew Association, a sort of Jewish YMCA. Two things 
shocked him about his new home: the diversity of the people on 
the streets and the fantastic range of foods in the grocery stores. 
He took photographs of the rows and rows of sausages in Man- 
hattan and mailed them to his mother in Moscow. “I’d never 
seen so many sausages,” he says. But once he’d marveled at the 
American cornucopia, he stepped back from it all and wondered 
just how necessary all of this food was. He read books about fast- 
ing and the effects of various highly restrictive diets. “I decided 
to look at it a little bit further and ask what is beneficial and what 



is not, he said. In the end he became a finicky vegetarian. “I 
don’t think all the energy you gain comes from food,” he says. 
“I think it comes from your environment.” 

He’d come to America with no money at all, and no real idea 
how to get it. He took a course on how to apply for a job. “It 
was quite frightening,” he says. “I didn’t speak English, really, 
and a resume was a totally alien concept.” His first interviewer 
asked Serge to tell him about himself. “To a Russian mental- 
ity, said Serge, that question means ‘Where are you born?’ 
‘Who are your siblings?’ ” Serge described for the man at great 
length how he had come from a long line of Jewish scholars 
and academics and nothing else. “He tells me I will hear from 
him again. I never do.” But he had an obvious talent for pro- 
gramming computers and soon found a job doing it, for $8.75 an 
hour, in a New Jersey medical center. From the medical center 
he landed a better job, in the Rutgers University computer sci- 
ence department, where, through some complicated combina- 
tion of jobs and grants, he was able to pursue a master’s degree. 
After Rutgers he spent a few years working at Internet start-ups 
until, in 1998, he received a job offer from a big New Jersey 
telecom company called IDT. For the next decade he designed 
computer systems and wrote the code to route millions of phone 
calls each day to the cheapest available phone lines. When he 
joined the company it had five hundred employees; by 2006 it 
had five thousand, and he was its star technologist. That year a 
headhunter called him and told him that there was fierce new 
demand on Wall Street for his particular skill: writing code that 
parsed huge amounts of information at great speed. 

Serge knew nothing about Wall Street and was in no par- 
ticular rush to learn about it. His singular talent was for mak- 
ing computers go fast, but his own movements were slow and 



deliberate. The headhunter pressed upon him a bunch of books 
about writing software on Wall Street, plus a primer on how to 
make it through a Wall Street job interview, and told him that, 
on Wall Street, he could make a lot more than the $220,000 a 
year he was making at the telecom company. Serge felt flattered, 
and liked the headhunter, but he read the books and decided 
Wall Street wasn’t for him. He enjoyed the technical challenges 
at the giant telecom and didn’t really feel the need to earn more 
money. A year later, in early 2007, the headhunter called him 
again. By this time IDT was in serious financial trouble; Serge 
was beginning to worry that the management was running the 
company into the ground. He had no savings to speak of. His 
wife, Elina, was carrying their third child, and they’d need to 
buy a bigger house. Serge agreed to interview with the Wall 
Street firm that especially wanted to meet him: Goldman Sachs. 

At least on the surface, Serge Aleynikov had the sort of life 
people are said to come to America for. He’d married a pretty 
fellow Russian immigrant and started a family with her. They’d 
sold their two-bedroom Cape-style house in Clifton, New Jer- 
sey, and bought a bigger colonial-style one in Little Falls. They 
had a nanny. They had a circle of Russians they called their 
friends. On the other hand, all Serge did was work, and his wife 
had no real clue what that work involved; they weren’t actually 
all that close to each other. He didn’t encourage people to get to 
know him well or exhibit a great deal of interest in getting to 
know them. He was acquiring a lot of possessions in which he 
had very little interest. The lawn in Clifton was a fair example 
of the general problem. When he’d gone hunting for his first 
house, he’d been enchanted by the idea of having his very own 
lawn. In Moscow such a thing was unheard of. The moment he 
owned a lawn, he regretted it. (“A pain in the butt to mow.”) A 



Russian writer named Masha Leder, who knew the Aleynikovs 
as well as anyone, thought of Serge as an exceptionally intel- 
lectually gifted but otherwise typical Russian Jewish computer 
programmer, for whom technical problems became an excuse 
not to engage with the messy world around him. “All of Serge’s 
life was some kind of mirage,” she said. “Or a dream. He was 
not aware of things. He liked slender girls who loved to dance. 
He married a girl and managed to have three kids with her 
before he figures out he doesn’t really know her. He was work- 
ing his ass off and she would spend the money he was mak- 
ing. He would come home and she would cook him vegetarian 
dishes. He was serviced, basically.” 

And then Wall Street called. Goldman Sachs put Serge 
through a series of telephone interviews, then brought him 
in for a long day of face-to-face interviews. These he found 
extremely tense, even a bit weird. “I was not used to seeing peo- 
ple put so much energy into evaluating other people,” he said. 
One after another, a dozen Goldman employees tried to stump 
him with brain teasers, computer puzzles, math problems, and 
even some light physics. It must have become clear to Goldman 
(it was to Serge) that he knew more about most of the things he 
was being asked than his interviewers did. At the end of the first 
day, Goldman invited him back for a second day. He went home 
and thought it over: He wasn’t all that sure he wanted to work 
at Goldman Sachs. “But the next morning I had a competitive 
feeling,” he says. “I should conclude it and try to pass it because 
it’s a big challenge.” 

He’d been surprised to find that in at least one way he fit in: 
More than half the programmers at Goldman were Russians. 
Russians had a reputation for being the best programmers on 
Wall Street, and Serge thought he knew why: They had been 



forced to learn to program computers without the luxury of 
endless computer time. Many years later, when he had plenty 
of computer time, Serge still wrote out new programs on paper 
before typing them into the machine. “In Russia, time on the 
computer was measured in minutes,” he said. “When you write 
a program, you are given a tiny time slot to make it work. Con- 
sequently we learned to write the code in ways that minimized 
the amount of debugging. And so you had to think about it a 
lot before you committed it to paper. . . . The ready availability 
of computer time creates this mode of working where you just 
have an idea and type it and maybe erase it ten times. Good 
Russian programmers, they tend to have had that one experi- 
ence at some time in the past — the experience of limited access 
to computer time.” 

He returned for another round of Goldman’s grilling, which 
ended in the office of a senior high-frequency trader — another 
Russian, Alexander Davidovich. The Goldman managing direc- 
tor had just two final questions for Serge, both designed to test 
his ability to solve problems. The first: Is 3,599 a prime number? 

Serge quickly saw that there was something strange about 
3,599: It was very close to 3,600. He jotted down the following 

3599 = (3600 - 1) = (60 2 - l 2 ) = (60 - 1) (60 + 1) = 59 x 61 
3599 = 59 x 61 

Not a prime number. 

The problem wasn’t that difficult, but, as he put it, “it was 
harder to solve the problem when you are anticipated to solve 
it quickly.” It might have taken him as long as two minutes to 



finish. The second question the Goldman managing director 
asked him was more involved, and involving. He described for 
Serge a room, a rectangular box, and gave him its three dimen- 
sions. He says there is a spider on the floor, and he gives me 
its coordinates. There is also a fly on the ceiling, and he gives 
me its coordinates as well. Then he asked the question: Calcu- 
late the shortest distance the spider can take to reach the fly.” 
The spider can’t fly or swing; it can only walk on surfaces. The 
shortest path between two points was a straight line, and so, 
Serge figured, it was a matter of unfolding the box, turning a 
three-dimensional object into a two-dimensional surface, then 
using the Pythagorean theorem to calculate the distances. This 
took him several minutes to work out; when he was done, 
Davidovich offered him a job at Goldman Sachs. His starting 
salary plus bonus came to $270,000. 

HE’D JOINED GOLDMAN at an interesting moment in the history of 
both the firm and Wall Street. By mid-2007 Goldman’s bond 
trading department was aiding and abetting a global financial 
crisis, most infamously by helping the Greek government to rig 
its books and disguise its debt, and by designing subprime mort- 
gage securities to fail, so that they might make money by betting 
against them. At the same time, Goldman’s equities department 
was adapting to radical changes in the U.S. stock market— just as 
that market was about to crash. A once sleepy oligopoly domi- 
nated by Nasdaq and the New York Stock Exchange was rapidly 
turning into something else. The thirteen public stock exchanges 
in New Jersey were all trading the same stocks. Within a few 
years there would be more than forty dark pools, two of them 
owned by Goldman Sachs, also trading the same stocks. 



The fragmentation of the American stock market was fueled, in 
part, by Reg NMS, which had also stimulated a huge amount of 
stock market trading. Much of the new volume was generated not 
by old-fashioned investors but by the extremely fast computers 
controlled by the high-frequency trading firms. Essentially, the 
more places there were to trade stocks, the greater the opportu- 
nity there was for high-frequency traders to interpose themselves 
between buyers on one exchange and sellers on another. This 
was perverse. The initial promise of computer technology was 
to remove the intermediary from the financial market, or at least 
reduce the amount he could scalp from that market. The reality 
turned out to be a windfall for financial intermediaries — of some- 
where between $10 billion and $22 billion a year, depending on 
whose estimates you wanted to believe. For Goldman Sachs, a 
financial intermediary, that was only good news. 

The bad news was that Goldman Sachs wasn’t yet making 
much of the new money. At the end of 2008, they told their 
high-frequency trading computer programmers that their trad- 
ing unit had netted roughly $300 million. That same year, the 
high-frequency trading division of a single hedge fund, Citadel, 
made $1.2 billion. The HFT guys were already known for hid- 
ing their profits, but a lawsuit between one of them, a Rus- 
sian named Misha Malyshev, and his former employer, Citadel, 
revealed that, in 2008, Malyshev had been paid $75 million in 
cash. Rumors circulated — they turned out to be true — of two 
guys who had left Knight for Citadel and guarantees of $20 mil- 
lion a year each. A headhunter who sat in the middle of the 
market and saw what firms were paying for geek talent says, 
“Goldman had started to figure it out, but they really hadn’t 
figured it out. They weren’t top ten.” 

The simple reason Goldman wasn’t making much of the big 



money now being made in the stock market was that the stock 
market had become a war of robots, and Goldman’s robots were 
slow. A lot of the moneymaking strategies were of the winner- 
take-all variety. When every player is trying to do the same 
thing, the player who gets all the money is the one whose com- 
puters can take in data and spit out the obvious response to it 
first. In the various races being run, Goldman was seldom first. 
That is why they had sought out Serge Aleynikov in the first 
place: to improve the speed of their system. There were many 
problems with that system, in Serge’s view. It wasn’t so much a 
system as an amalgamation. “The code development practices at 
IDT were much more organized and up-to-date than at Gold- 
man,” he says. Goldman had bought the core of its system fifteen 
years earlier in the acquisition of one of the early electronic trad- 
ing firms, Hull Trading. The massive amounts of old software 
(Serge guessed that the entire platform had as many as 60 mil- 
lion lines of code in it) and fifteen years of fixes to it had created 
the computer equivalent of a giant rubber-band ball. When one 
of the rubber bands popped, Serge was expected to find it and 
fix it. 

Goldman Sachs often used complexity to advantage. The firm 
designed complex subprime mortgage securities that others did 
not understand, for instance, and then took advantage of the 
ignorance they had introduced into the marketplace. The auto- 
mation of the stock market created a different sort of complex- 
ity, with lots of unintended consequences. One small example: 
Goldman’s trading on the Nasdaq exchange. In 2007, Goldman 
owned the (unmarked) building closest to Nasdaq. The build- 
ing housed Goldman’s dark pool. When Serge arrived, tens of 
thousands of messages per second were flying back and forth 
between computers inside the two buildings. Proximity, he 



assumed, must offer Goldman Sachs some advantage — after all, 
why else buy the building closest to the exchange? But when he 
looked into it he found that, to cross the street from Goldman to 
Nasdaq, a signal took 5 milliseconds, or nearly as much time as 
it would take, a couple of years later, for a signal to travel on the 
fastest network from Chicago to New York. “The theoretical 
limit [of sending a signal] from Chicago to New York and back 
is something like seven milliseconds,” said Serge. “Everything 
more than that is the friction caused by man.” The friction could 
be caused by physical distance — say, if the signal moving across a 
street in Carteret traveled in something less direct than a straight 
line. It could be caused by computer hardware. But it could also 
be caused by slow, clunky software — and that was Goldman’s 
problem. Their high-frequency trading platform was designed, 
in typical Goldman style, as a centralized hub-and-spoke system. 
Every signal sent was required to pass through the mother ship 
in Manhattan before it went back out into the marketplace. “But 
the latency [the 5 milliseconds] wasn’t mainly due to the physi- 
cal distance,” says Serge. “It was because the traffic was going 
through layers and layers of corporate switching equipment.” 

Broadly speaking, there were three problems Serge had been 
hired to solve. They corresponded to the three stages of an elec- 
tronic trade. The first was to create the so-called ticker plant, 
or the software that translated the data from the thirteen public 
exchanges so that it could be viewed as a single stream. Reg 
NMS had imposed on the big banks a new obligation: to take in 
the information from all the exchanges in order to ensure that 
they were executing customers’ orders at the official best market 
price — the NBBO. If Goldman Sachs purchased 500 shares of 
IBM at $20 a share on the New York Stock Exchange on behalf 
of a customer without first taking the 100 shares of IBM offered 



at $19.99 on the BATS exchange, they’d have violated the regu- 
lation. The easiest and cheapest solution for the big banks to this 
problem was to use the combined data stream created by public 
exchanges — the SIP. Some of them did just that. But to assuage 
the concerns of their customers that the SIP was too slow and 
offered them a dated view of the market, a few banks promised 
to create a faster data stream — but nothing they created for cus- 
tomers’ orders was as fast as what they created for themselves. 

Serge had nothing to do with anything used by Goldman’s 
customers. His job was to build the system that Goldman Sachs’s 
own proprietary traders would use in their activities — and it 
went without saying that it needed to be faster than anything 
used by the customers. The first and most obvious thing he did 
to make Goldman’s robots faster was exactly what he had done 
at IDT to enable millions of phone calls to find their cheapest 
route: He decentralized Goldman’s system. Rather than have 
signals travel from the various exchanges back to the Goldman 
hub, he set up separate mini-Goldman hubs inside each of the 
exchanges. To acquire the information for its private ticker plant, 
Goldman needed to place its computers as close as possible to the 
exchange’s matching engine. The software that took the out- 
put from the ticker plant and used it to figure out smart trades 
in the stock market was the second stage of the process: Serge 
rewrote a lot of that code to make it run faster. The third stage 
was called “order entry.” As it sounds, this was the software that 
sent those trades back out into the market to be executed. Serge 
worked on that, too. He didn’t think of it this way, but in effect 
he was building a high-frequency trading firm within Goldman 
Sachs. The speed he created for Goldman Sachs could be used 
for many purposes, of course. It could be used simply to execute 
Goldman’s prop traders’ smart strategies as quickly as possible. 



It could also be used by Goldman’s prop traders to trade the 
slow-moving customer orders in their own dark pool against 
the wider market. The speed Serge gave them could be used, for 
example, to sell Chipotle Mexican Grill to Rich Gates at a high 
price in the dark pool while buying it from him at a lower price 
on a public exchange. 

Serge actually didn’t know what the speed was being used for 
by Goldman’s prop traders. As he worked, he became aware of 
a gulf in understanding between himself and his employer. The 
people at Goldman with whom he dealt understood the effects 
of what he did but not their deep causes. No one at Goldman 
had a global view of the firm’s computer software, for instance: 
He figured that out on the first day, when they asked him to look 
into the code base and figure out how the different components 
talked to each other. In doing so, he saw that there was shock- 
ingly little documentation left behind by the people who had 
written that code, and that no one at Goldman could explain 
it to him. He, in turn, was not privy to the commercial effects 
of his actions — in part, he sensed, because his superiors did not 
want him to know them. “I think it is done intentionally,” he 
said. “The less you know about how they make the money, the 
better it is for them.” 

But even if they had wanted him to know how the money was 
made, it is unclear Serge would have cared to know. “I think the 
engineering problems are much more interesting than the busi- 
ness problems,” he says. “Finance is just who gets money. Does 
it wind up in the right pocket or the left pocket? It just so hap- 
pens that the companies that make money are the companies like 
Goldman Sachs. You can’t really win in that game unless you 
are one of these people.” He understood that Goldman’s quants 
were forever dreaming up new trading strategies, in the form of 



algorithms, for his robots to execute, and that these traders were 
meant to be extremely shrewd. He grasped further that “all their 
algorithms are premised on some sort of prediction — predicting 
something one second into the future.” But you needed only 
to observe the 2008 stock market crash from inside of Gold- 
man Sachs, as Serge had, to see that what seemed predictable 
often was not. Day after volatile day in September 2008, Gold- 
man’s supposedly brilliant traders were losing tens of millions 
of dollars. “All of the expectations didn’t work,” recalls Serge. 
“They thought they controlled the market, but it was an illu- 
sion. Everyone would come into work and were blown away by 
the fact that they couldn’t control anything at all. . . . Finance 
is a gambling game for people who enjoy gambling.” He wasn’t 
a gambler by nature. He preferred the deterministic world of 
programming to the pseudo-deterministic world of speculation, 
and he never fully grasped the connection between his work and 
the Goldman traders’. 

What Serge did know about Goldman’s business was that the 
firm’s position in the world of high-frequency trading was inse- 
cure. “The traders were always afraid of the small HFT shops,” 
as he put it. He was making Goldman’s bulky, inefficient sys- 
tem faster, but he could never make it as fast as a system built 
from scratch, without the burden of 60 million lines of old code 
underneath it. Or a system that, to change it in any major way, 
did not require six meetings and signed documents from infor- 
mational security officers. Goldman hunted in the same jungle 
as the small HFT firms, but it could never be as quick or as 
nimble as those firms: No big Wall Street bank could. The only 
advantage a big bank enjoyed was its special relationship to the 
prey: its customers. (As the head of one high-frequency trading 
firm put it, “When one of these people from the banks inter- 



views with us for a job, he always talks about how smart his 
algos are, but sooner or later he’ll tell you that without his cus- 
tomer he can’t make any money.”) 

After a few months working on the forty-second floor at 
One New York Plaza, Serge came to the conclusion that the 
best thing they could do with Goldman’s high-frequency trad- 
ing platform was to scrap it and build a new one from scratch. 
His bosses weren’t interested. “The business model of Goldman 
Sachs was, if there is an opportunity to make money right away, 
let’s do that,” he says. “But if there was something long-term, 
they weren’t that interested.” Something would change in the 
stock market — an exchange would introduce a new, complicated 
rule, for instance — and that change would create an immediate 
opportunity to make money. “They’d want to do it immedi- 
ately,” says Serge. “But if you think about it, it’s just patching the 
existing system constantly. The existing code base becomes an 
elephant that’s difficult to maintain.” 

That is how he spent the vast majority of his two years at 
Goldman, patching the elephant. For their patching material 
he and the other Goldman programmers resorted, every day, 
to open source software — software developed by collectives of 
programmers and made freely available on the Internet. The 
tools and components they used were not specifically designed 
for financial markets, but they could be adapted to repair Gold- 
man’s plumbing. He discovered, to his surprise, that Goldman 
had a one-way relationship with open source. They took huge 
amounts of free software off the Web, but they did not return it 
after he had modified it, even when his modifications were very 
slight and of general, rather than financial, use. “Once I took 
some open source components, repackaged them to come up 
with a component that was not even used at Goldman Sachs,” 



he says. “It was basically a way to make two computers look 
like one, so if one went down the other could jump in and 
perform the task.” He’d created a neat way for one computer 
to behave as the stand-in for another. He described the pleasure 
ot his innovation this way: “It created something out of chaos. 
When you create something out of chaos, essentially, you reduce 
the entropy in the world.” He went to his boss, a fellow named 
Adam Schlesinger, and asked if he could release it back into 
open source, as was his inclination. “He said it was now Gold- 
man’s property,” recalls Serge. “He was quite tense.” 

Open source was an idea that depended on collaboration and 
sharing, and Serge had a long history of contributing to it. He 
didn’t fully understand how Goldman could think it was okay 
to benefit so greatly from the work of others and then behave so 
selfishly toward them. “You don’t create intellectual property,” 
he said. “You create a program that does something.” But from 
then on, on instructions from Adam Schlesinger, he treated 
everything on Goldman Sachs’s servers, even if it had just been 
transferred there from open source, as Goldman Sachs’s prop- 
erty. (Later, at his trial, his lawyer flashed two pages of computer 
code: the original, with its open source license on top, and a 
replica, with the open source license stripped off and replaced by 
the Goldman Sachs license.) 

The funny thing was that Serge actually liked Adam Schles- 
inger, and most of the other people he worked with at Goldman. 
He liked less the environment the firm created for them to work 
in. “Everyone lived for the year-end number,” he said. “You 
get satisfied when the bonus is sizable and you get not satisfied 
when the number is not. Everything there is very possessive.” It 
made no sense to him the way people were paid individually for 
achievements that were essentially collective achievements. “It 



was quite competitive. Everyone’s trying to show how good their 
individual contribution to the team is. Because the team doesn’t 
get the bonus, the individual does.” 

More to the point, he felt that the environment Goldman 
created for its employees did not encourage good programming, 
because good programming required collaboration. “Essentially 
there was very minimal connections between people,” he says. 
“In telecom you usually have some synergies between people. 
Meetings when people exchange ideas. They aren’t under stress 
in the same way. At Goldman it was always, ‘Some component is 
broken and we’re losing money because of it. Fix it now.’ ” The 
programmers assigned to fix the code sat in cubicles and hardly 
spoke to one another. “When two people wanted to talk they 
wouldn’t just do it out on the floor,” says Serge. “They would go 
to one of the offices around the floor and close the door. I never 
had that experience in telecom or academia.” 

By the time the financial crisis hit, Serge had a reputation 
of which he himself was unaware: He was known to corpo- 
rate recruiters outside Goldman as the best programmer in the 
firm. “There were twenty guys on Wall Street who could do 
what Serge could do,” says a headhunter who recruits often for 
high-frequency trading firms. “And he was one of the best, 
if not the best.” Goldman also had a reputation in the mar- 
ket for programming talent— for keeping its programmers in 
the dark about their value to the firm’s trading activities. The 
programmer types were different from the trader types. The 
trader types were far more alive to the bigger picture, to their 
context. They knew their worth in the marketplace down to 
the last penny. They understood the connection between what 
they did and how much money was made, and they were good 
at exaggerating the importance of the link. Serge wasn’t like 



that. He was a little-picture person, a narrow problem solver. 
“1 think he didn’t know his own value,” says the recruiter. 
“He compensated for being narrow by being good. He was 
that good.” 

Given his character and his situation, it’s hardly surprising 
that the market kept finding Serge Aleynikov and telling him 
what he was worth, rather than the other way around. A few 
months into his new job, headhunters were calling him every 
other week. A year into his new job, he had an offer from UBS, 
the Swiss bank, and a promise to bump up his salary to $400,000 
a year. Serge didn’t particularly want to leave Goldman Sachs 
just to go and work at another big Wall Street firm, and so when 
Goldman offered to match the offer, he stayed. But in early 2009 
he had another call, with a very different kind of offer: to cre- 
ate a trading platform from scratch for a new hedge fund run by 
Misha Malyshev. 

The prospect of creating a new platform, rather than con- 
stantly patching an old one, excited him. Plus Malyshev was 
willing to pay him more than a million dollars a year to do it, 
and he suggested that they might even open an office for Serge 
near his home in New Jersey. Serge accepted the job offer and 
then told Goldman he was leaving. “When I put in the resigna- 
tion letter,” he said, “everyone comes to me one by one. The 
common perception was that if they had the right opportunity 
to quit Goldman they would do that in no time.” Several hinted 
to him how much they would like to join him at his new firm. 
His bosses asked him what they could do to persuade him to 
stay. “They were trying to pursue me into this monetary discus- 
sion,” says Serge. “I told them it wasn’t the money. It was the 
chance to build a new system from the ground up.” He missed 
his telecom work environment. “Whereas at IDT I was really 



seeing the results of my work, here you had this monstrous sys- 
tem and you are patching it right and left. No one is giving you 
the whole picture. I had a feeling no one at Goldman really 
knows how it works as a whole, and they are just uncomfortable 
admitting that.” 

He agreed to hang around for six weeks and teach other Gold- 
man people everything he knew, so that they could continue 
to find and fix the broken bands in their gigantic rubber ball. 
Four times in the course of that last month he mailed himself 
source code he was working on. The files contained a lot of 
open source code he had worked with, and modified, over the 
past two years, mingled with code that wasn’t open source but 
was obviously proprietary to Goldman Sachs. He hoped to dis- 
entangle one from the other in case he needed to remind him- 
self how he had done what he had done with the open source 
code; he might need to do it again. He sent these files the same 
way he had sent himself files nearly every week since his first 
month on the job at Goldman. “No one had ever said a word 
to me about it,” he says. He pulled up his browser and typed 
into it the words: “free subversion repository.” Up popped a list 
of places that stored code for free and in a convenient fashion. 
He clicked the first link on the list. To find a place to send the 
code took about eight seconds. And then he did what he had 
always done since he’d first started programming computers: He 
deleted his bash history — the commands he had typed into his 
own Goldman computer keyboard. To access the computer, he 
was required to type his password. If he didn’t delete his bash 
history, his password would be there to see, for anyone who had 
access to the system. 

It wasn’t an entirely innocent act. “I knew that they wouldn’t 
be happy about it,” he said, because he knew their attitude was 



that anything that happened to be on Goldman’s servers was the 
wholly owned property of Goldman Sachs — even when Serge 
himself had taken that code from open source. When asked how 
he felt when he did it, he says, “It felt like speeding. Speeding 
in the car.” 

FOR MUCH OF the flight from Chicago he’d slept. Leaving the 
plane, he noticed three men in dark suits waiting in the alcove 
of the Jetway reserved for baby strollers and wheelchairs. They 
confirmed his identity, explained that they were from the FBI, 
handcuffed him, searched his pockets, removed his backpack, 
told him to remain calm, and then walled him oft' from the 
other passengers. This last act was no great feat. Serge was 
six feet tall but weighed roughly 140 pounds: To hide him 
you needed only to turn him sideways. He resisted none of 
these actions, but he was genuinely bewildered. The men in 
black refused to tell him his crime. He tried to guess it. His 
first guess was that they’d gotten him mixed up with some 
other Sergey Aleynikov. Next it occurred to him that his new 
employer, Misha Malyshev, then being sued by Citadel, might 
have done something shady. Wrong on both counts. It wasn’t 
until the plane had emptied and they’d escorted him into 
Newark Airport that they told him his crime: stealing com- 
puter code owned by Goldman Sachs. 

The agent in charge of the case, Michael McSwain, was new 
to law enforcement. Oddly enough, he’d spent twelve years, 
until 2007, working as a currency trader on the Chicago Mer- 
cantile Exchange. He and others like him had been put out of 
business by Serge and people like him — or, more exactly, by the 
computers that had replaced the traders on the floors of every 



U.S. exchange. It wasn’t an accident that McSwain’s career on 
Wall Street ended the same year that Serge’s began. 

McSwain marched Serge into a black town car and drove him 
to the FBI building in lower Manhattan. After making a show 
of stashing his gun, McSwain led him into a tiny interrogation 
room, handcuffed him to a rod on the wall, and, finally, read 
him his Miranda rights. Then he explained what he knew, or 
thought he knew: In April 2009 Serge had accepted a job at a 
new high-frequency trading shop, Teza Technologies, but had 
remained at Goldman for the next six weeks. Between early 
April and June 5, when Serge left Goldman for good, he sent 
himself, through the so-called subversion repository, 32 mega- 
bytes of source code from Goldman’s high-frequency stock trad- 
ing system. McSwain clearly found it damning that the website 
Serge used was called a subversion repository, and that it was 
in Germany. He also seemed to think it significant that Serge 
had used a site not blocked by Goldman Sachs, even after Serge 
tried to explain to him that Goldman did not block any sites 
used by its programmers but merely blocked its employees from 
porn sites and social media sites and suchlike. Finally, the FBI 
agent wanted him to admit that he had erased his bash history. 
Serge tried to explain why he always erased his bash history, but 
McSwain had no interest in his story. “The way he did it seemed 
nefarious,” the FBI agent would later testify. 

All of which was true, as far as it went, but, to Serge, that 
didn’t seem very far. “I thought it was like, crazy, really,” he 
says. “He was stringing these computer terms together in ways 
that made no sense. He didn’t seem to know anything about 
high-frequency trading or source code.” For instance, Serge had 
no idea where the subversion repository was physically located. 
It was just a place on the Internet used by developers to store the 



code they were working on. “The whole point of the Internet 
is to abstract the physical location of the server from its logi- 
cal address,” he said. To Serge, McSwain sounded like a man 
repeating phrases that he’d heard from others but that to him 
actually meant nothing. “There is a game in Russia called Bro- 
ken Phone,” he said — a variation on the American game Tele- 
phone. “It felt like he was playing that.” 

What Serge did not yet know was that Goldman had dis- 
covered his downloads — of what appeared to be the code they 
used for their proprietary high-speed stock market trading — -just 
a few days earlier, even though Serge had sent himself the first 
batch of code months ago. They’d called the FBI in haste and 
had put McSwain through what amounted to a crash course in 
high-frequency trading and computer programming. McSwain 
later conceded that he didn’t seek out independent expert advice 
to study the code Serge Aleynikov had taken, or seek to find 
out why he might have taken it. “I relied on statements from 
Goldman employees,” he said. He had no idea himself of the 
value of the stolen code (“representatives from Goldman told 
me it was worth a lot of money”), or if any of it was actually 
all that special (“representatives of Goldman Sachs told us there 
were trade secrets in the code”). The agent noted that the Gold- 
man files were on both the personal computer and the thumb 
drive that he’d taken from Serge at Newark Airport, but he 
failed to note that the files remained unopened. (If they were so 
important, why hadn’t Serge looked at them in the month since 
he’d left Goldman?) The FBI’s investigation before the arrest 
consisted of Goldman explaining some extremely complicated 
stuff to McSwain that he admitted he did not fully understand — 
but trusted that Goldman did. Forty-eight hours after Goldman 
called the FBI, McSwain arrested Serge. Thus the only Gold- 



man Sachs employee arrested by the FBI in the aftermath of 
a financial crisis Goldman had done so much to fuel was the 
employee Goldman asked the FBI to arrest. 

On the night of his arrest, Serge waived his right to call a 
lawyer. Fie called his wife, told her what had happened, and said 
that a bunch of FBI agents were on the way to their home to 
seize their computers, and to please let them in, although they 
had no search warrant. Then he sat down and politely tried to 
clear up the confusion of this FBI agent who had arrested him 
without an arrest warrant. “Flow could he figure out if this was 
a theft if he didn’t understand what was taken?” he recalls having 
asked himself. What he’d done, in his view, was trivial; what he 
stood accused of — violating both the Economic Espionage Act 
and the National Stolen Property Act — did not sound trivial at 
all. Still, he thought that it the agent understood how computers 
and the high-frequency trading business actually worked, he’d 
apologize and drop the case. “The reason I was explaining it to 
him was to show that there was nothing there,” he said. “Fie 
was completely not interested in the content of what I am say- 
ing. He just kept saying to me, ‘If you tell me everything, I’ll 
talk to the judge and he’ll go easy on you.’ It appeared they had 
a very strong bias from the very beginning. They had goals they 
wanted to fulfill. One was to obtain an immediate confession.” 

The chief obstacle to the FBI’s ability to extract his confes- 
sion, oddly, wasn’t Serge’s willingness to provide it but its own 
agent’s ignorance of the behavior to which Serge was attempting 
to confess. “In the written statement he was making some very 
obvious mistakes, computer terms and so on,” recalled Serge. 
“I was saying, ‘You know, this is not correct.’” Serge patiently 
walked the agent through his actions. At 1:43 in the morning on 
July 4, after five hours of discussion, McSwain sent a giddy one- 



line email to the U.S. Attorney’s office: “Holy crap he signed a 

Two minutes later, he dispatched Serge to a cell in the Metro- 
politan Detention Center. The prosecutor, Assistant U.S. Attor- 
ney Joseph Facciponti, argued that Serge Aleynikov should be 
denied bail. The Russian computer programmer had in his pos- 
session computer code that could be used “to manipulate mar- 
kets in unfair ways.” The confession Serge had signed, scarred by 
phrases crossed out and rewritten by the FBI agent, later would 
be presented by prosecutors to a jury as the work of a thief who 
was being cautious, even tricky, with his words. “That’s not 
what happened,” said Serge. “The document was being crafted 
by someone with no previous expertise in the matter.” 

Sergey Aleynikov’s signed confession was the last anyone heard 
from him, at least directly. He declined to speak to reporters or 
testify at his trial. He had a halting manner, a funny accent, a 
beard, and a physique that looked as if it had been painted by El 
Greco: In a lineup of people chosen randomly from the streets, 
he was the guy most likely to be identified as the Russian spy, or 
a character from the original episodes of Star Trek. In technical 
discussions he had a tendency to speak with extreme precision, 
which was great when he was dealing with fellow experts but 
mind-numbing to a lay audience. In the court of U.S. public 
opinion, he wasn’t well suited to defend himself, and so, on the 
advice of his attorney, he didn’t. He kept his long silence even 
after he was sentenced, without the possibility of parole, to eight 
years in a federal prison. 



R onan didn’t intend to tell his father exactly how much 
money he made, or anything else that sounded like boast- 
ing, but he wanted him to know he needn’t worry about 
his son any longer. For Christmas, in 2011, he’d fly back to 
Ireland, as he did every year, only this year he’d travel toward 
a conversation. He felt no particular attachment to the place. 
“I don’t belong there at all,” he said. “There’s fucking fat kids 
everywhere. When I was growing up there was no fat kids. It’s 
lost its charm.” He missed his family, nothing more. When he 
arrived at their house in the Dublin suburbs, his parents would 
be waiting with a list of their stuff that needed to be repaired or 
reprogrammed. After he’d rebooted their computer, or recap- 
tured their satellite signal, he’d sit down with them and have this 
talk. “American parents get into their fucking kids’ business,” 
said Ronan. “In Ireland they don’t. They mind their own fuck- 
ing business.” His father still had no clear idea what he did for a 
living, or, for that matter, why a big Wall Street bank would find 



him useful. “He didn’t think I was a fucking teller or something. 
But if I said to my dad, ‘I’m a trader,’ he’d say, ‘What the fuck do 
you know about trading?’ ” His life was his life, theirs was theirs. 
“My mom and dad, I know they love me. It’s just Irish love. And 
I just kinda wanted him to know I was legit in this business. It 
was semi to set him at ease. I didn’t want him to think I was 
putting the family in jeopardy.” 

Ireland’s economy had collapsed three years earlier, under the 
weight of a lot of American-style financial machinations and bad 
advice from American financiers. Many of Ronan’s childhood 
friends were still out of work. It didn’t seem like the best time to 
be taking a risk. Just days before Ronan was to fly back to Ire- 
land, however, Brad Katsuyama had pulled him into a meeting 
with John Schwall and Rob Park. Brad had wanted to know, if 
he left RBC to create a new stock exchange, who might leave 
with him. They’d taken turns answering the same question: You 
in? On some level, Ronan could not believe what he was hear- 
ing as he listened to the sound of his own voice: He’d spent his 
entire career trying to get a job on Wall Street, and now that he 
finally had one, the guy who had given it to him was asking him 
to throw it away. On another level, the question answered itself. 
“Too much was riding on me,” he said. “And I felt like I owed 
Brad. He was the one who gave me a chance. I trusted him: He’s 
not a fucking idiot.” 

By the end of 2011, there was something else on Ronan’s 
mind, too. He’d now seen Wall Street from the inside. It wasn’t 
as persuasive to him as he had expected it to be. “It’s like if I stay 
here I’ll become full of shit,” he said. 

They were all very much in; what they were in for was less 
clear. Until they found someone willing to pay for the building 
of a new stock exchange, they couldn’t very well quit their jobs to 



do it. Ronan’s commitment to Brad was less a promise of imme- 
diate action than a promissory note to be cashed at some point in 
the indefinite future. But they did have a goal: to restore fairness 
to the U.S. stock market — for the first time in Wall Street his- 
tory, perhaps, to institutionalize fairness. And they had a rough 
idea: to deploy Thor as the backbone of a strange new kind of 
stock exchange, to which brokers could send stock market orders 
so that Thor might route them to all the other exchanges. And 
yet none of them, least of all Ronan, believed that Thor alone 
could change the stock market, mainly because they doubted 
that the big brokerage firms would hand over their most valu- 
able commodity (their customers’ stock market orders) to any 
third party to execute. They also suspected that other forms of 
unfairness plagued the market, problems that Thor didn’t begin 
to address. “I give what we have right now a ten percent chance 
of working,” Ronan told his colleagues. “But with the four of us 
I give us a seventy percent chance of figuring it out.” 

After he left Brad’s office, Ronan realized that the talk he 
wanted to have with his father had changed: He needed his 
father’s advice. He’d already taken one big risk, when he had 
quit a telecom job in which he’d made nearly half a million a 
year for a Wall Street job that paid him a third of that. It had 
panned out: RBC had just handed him a bonus of nearly a mil- 
lion bucks and was asking him if he would like to run the more 
lucrative half of their stock market trading operation. (“They 
told me I could name my price.”) As his plane dipped toward 
the Irish coast, he wanted to know if he was out of his mind to 
quit his $910,000-a-year job for one that paid $2,000 a month — 
money that would quite possibly be paid to him out of funds he 
himself invested in the new company. His father might not care 
to know the details, but he’d grasp the gist of his predicament. 



“I wanted to ask him: ‘Is there a time when you stop rolling the 
dice?’ I didn’t know if RBC was that time.” But when he finally 
sat his father down, Ronan realized he couldn’t explain even the 
gist of his predicament unless he confessed the size of his bonus. 
“When I was telling him I’d made nine hundred and ten thou- 
sand dollars he about had a fucking heart attack,” said Ronan. “I 
mean, he doubled over in his chair.” 

At length his father recovered, then looked up at his son and 
said, “You know what, Ro, your risks seem to have paid off so 
far. Why the fuck not?” 

Ronan landed back in New York on Tuesday, January 3, 
2012, turned on his BlackBerry, and watched the new messages 
flood in. The first was from Brad, announcing his resignation 
from the Royal Bank of Canada. As Ronan later recalled the 
moment, “The next ten messages said, ‘Holy shit, Brad Kat- 
suyama just fucking resigned.’ ” Ronan knew that RBC’s bosses 
up in Canada had been refusing, artfully, to deal with Brad’s 
insistence that it would be better for all concerned if he not only 
quit the bank to pursue an idea he had conceived whde working 
for the bank but also took several of the bank’s most valuable 
employees with him. The bosses in Canada clearly didn’t like 
the sound of any part of this. They assumed that if they stalled 
for time, Brad would come to his senses. What kind of Wall 
Street trader quits a secure $2-million-plus-a-year job to start 
a risky business — a business for which he doesn’t have even the 
financial backing? 

At baggage claim, Ronan reached Brad by phone. “I just 
wanted to ask him: What the fuck is going on?’ ” Brad told him, 
in surprisingly few words: He was tired of all these supposedly 
important people who ran this supposedly important bank nod- 
ding politely when he tried to speak to them about something 



that was far, far more important than any one person or any one 
bank. “They were thinking he’d never do it,” said Ronan. “And 
he was like, ‘Oh yeah, motherfucker?’ And he did it!” When 
Ronan rang off, he thought: Well, he’s pushed me all in. 

BRAD GOT TO work around 6:30 every morning. That first morn- 
ing after the Christmas break, he went to his immediate superior 
and told him that he was done. Then he went to his desk and 
wrote one email to Ronan, Rob Park, and John Schwab, and 
another to three senior guys in Canada. Five minutes later his 
phone rang. It was Canada, outraged. What the hell are you doing? 
asked the senior manager on the other end of the line. You can’t 
do this. To which Brad said: I just did. 

He left the bank with nothing — no paper, no code, no cer- 
tainty that anyone would actually follow him out, and not even, 
as it turned out, a clear idea for a business. Like everyone else 
in the stock market, Brad had received a jolt when he read that 
a Goldman Sachs high-frequency programmer had gone to 
jail for mailing himself computer code. Goldman’s sensitivity 
confirmed his suspicion that, around 2009, the big Wall Street 
banks, previously distracted by the financial crisis, had finally 
woken up to the value of the customer orders inside their own 
dark pools. They were using fear and intimidation to control 
the technologists who, ultimately, could exploit that value; and 
the culture of finance suddenly was becoming more closed and 
secretive — which was saying something. The people who now 
did what Ronan had once done for the big banks and HFT 
firms, for instance, would not be allowed to see and hear all 
that Ronan had been allowed to see and hear. And the banks 
were now using the legal system to make it harder for their 



more technical employees to leave. “I said to Rob, ‘No fucking 
around,’ ” recalled Brad. “He said, ‘Don’t worry. There’s noth- 
ing I’d want to take from here anyway.’ ” 

They’d be starting fresh. They could use the insights about 
the stock market gained from Thor, but Thor itself belonged 
to the Royal Bank of Canada. Their main advantage — their 
only sustainable advantage — was that investors trusted them. 
The investors on the receiving end of Wall Street’s sales pitches 
were not, by nature, trusting; or, if they were trusting by nature, 
their natures were reshaped by their environment. People on 
Wall Street were simply paid too much to lie and dissemble and 
obfuscate, and so every trusting feeling in the financial markets 
simply had to be followed by a trailing doubt. Something about 
Brad had led investors to lower their guard and to trust him. 
Whatever that was, it was sufficiently powerful that a group of 
people who ran some of the world’s biggest mutual funds and 
hedge funds, and who controlled roughly one third of the entire 
United States stock market, petitioned his superiors at RBC, 
after he had quit, to allow him to leave, so that he might restore 
trust to the financial markets on a grander scale. 

And yet — even as he walked away from millions of Wall 
Street dollars — some of these very people raised questions about 
his motives. He needed $10 million or so to hire the people who 
could help him to design his new stock market, and to write the 
computer code that would be the basis for that market. He’d 
hoped — assumed, even — that these big investors would supply 
him with the capital to build the new stock exchange, but eight 
of every ten pitch meetings began with some version of the same 
question: “Why are you doing this? Why are you attacking a 
system that has made you rich and will make you even richer if 
you just go along with it?” As one investor put it, behind Brad’s 



back, “I have a question about Brad: Have you figured out why 
he’s playing Robin Hood?” 

Brad’s first answer to that question was the thing he’d told 
himself: The stock market had become grotesquely unjust, and 
badly needed to be changed, and he’d come to see that, if he 
didn’t do it, no one else would. “That didn’t sit well,” he recalled. 
“They’d just say, ‘That sounds like complete bullshit.’ The first 
couple of times it happened, it really bothered me.” Then he got 
over it. If this new stock exchange flourished, its founders stood 
to make money — maybe a lot of money. He wasn’t a monk; he 
simply didn’t feel any need to make great sums of money. But 
he noticed, weirdly, that when he stressed how much money 
he himself might make from the new stock exchange, potential 
investors in his new business warmed to him — and so he started 
to stress how much money he might make. “We had a saying 
that seemed to appease everyone when they asked why we are 
doing this,” he said. “We are long-term greedy. That worked very 
well. ... It always got a better response out of them than my 
first answer.” 

He spent six months running around New York faking greed 
he didn’t really feel, to put money people at ease. It was mad- 
dening: He couldn’t get the people who should give him money 
to do so, and he couldn’t take the money from the people who 
wanted to give it to him. Just about all of the big Wall Street 
banks either asked him outright if they might buy a stake in his 
exchange or wanted at least to be considered as possible inves- 
tors. But if he took their money, his stock exchange would lose 
both its independence and its credibility with investors. His 
friends and family in Toronto also all wanted to invest in his 
new company. They presented a different issue. Two hours after 
Brad had let them know, via email, that he was pounding the 



pavement to raise money for a new stock market, they ponied 
up, collectively, $1.5 million. Some of these people could afford 
to take risks with their money, but some had no more than a few 
thousand dollars in savings. Before he allowed them to invest, 
Brad insisted that they send him bank statements to prove that 
they could afford to lose whatever they invested. “Your brother 
has never failed at anything he has ever done,” one old friend 
wrote to Brad’s older brother, Craig, to explain why the new 
business wasn’t at all risky, and to ask him to intercede on his 
behalf and overrule Brad’s decision not to take his money. 

What he needed was for the big stock market investors who 
had said they wanted him to quit RBC to fix the stock market — 
that is, the mutual funds, pension funds, and hedge funds — to 
put their money where their mouth was. They offered all sorts 
of excuses why they couldn’t help: They weren’t designed to 
invest in start-ups; the investment managers thought it was a 
great idea, but the compliance arm simply wasn’t equipped to 
evaluate Brad; and so on. “The amount of money we were ask- 
ing for was so small that it was too much of a pain in the ass 
for them to figure out how to give it to us,” said Brad. They 
all wanted him to build his exchange; they all hoped to benefit 
from that exchange; but they all also assumed that someone else 
would supply the capital to do it. Many had good excuses — 
it was indeed outside the mission of a giant pension fund to 
invest in start-ups. Still, it was disappointing. “They’re like one 
of those fucking friends who say he’ll back you up in a fight and 
they don’t do anything,” said Ronan, after one long and frustrat- 
ing day of begging for capital. “You’re on the ground, bloody, 
and only then do they jump in and throw a punch.” 

Some of them were like that; but not all of them. The giant 
mutual fund manager Capital Group pledged to invest — on the 



condition that they weren’t the lone investor but part of a con- 
sortium; so did another, Brandes Investment Partners. And there 
were several that voiced a sound objection: The business Brad 
was pitching to them was a foggy proposition — a stock exchange 
that existed mainly to route their stock market orders to all the 
other exchanges. How would that work? Thor had worked great, 
but why did Brad imagine that the predators who operated with 
such abandon on America’s public and private exchanges would 
not adapt to it? And why did he think Wall Street’s biggest banks 
would subcontract the routing of their stock market orders to his 
new exchange? Because it was “fair”? The banks’ salesmen ran 
around every day selling the banks’ own routers. They weren’t 
going to turn on a dime and say, “Oh yeah, we’ve been paid 
huge sums of money to sell you out to high-frequency traders, 
but now we’re going to give all the stock market orders to Brad, 
so we can’t sell you out any longer.” 

Brad didn’t fully understand the enterprise he needed to cre- 
ate until the market forced him to, by not giving him the capital 
for the enterprise he thought he wanted to create. Fuller under- 
standing arrived in August 2012, in a meeting with David Ein- 
horn, who ran the hedge fund Greenlight Capital. After listening 
to Brad’s pitch, Einhorn asked him a simple question: Why aren’t 
we all just picking the same exchange? Why didn’t investors organize 
themselves to sponsor a single stock exchange entrusted with 
guarding their interests and protecting them from Wall Street 
predators? There’ d never been any collective pressure brought 
by investors on the big banks to route their stock market orders 
to any one exchange, but that was only because there was no 
good reason to prefer one exchange over another: The fifty or so 
places on which stocks were traded were all designed by finan- 
cial intermediaries, for financial intermediaries. “It was so obvi- 



ous it was almost embarrassing,” said Brad. “That should have 
been our pitch: not that we should route the orders using Thor 
but [that] we should create the one place investors would choose 
to go.” That is, they shouldn’t simply seek to defend investors 
on the existing stock exchanges. They should seek to put all the 
other exchanges out of business. 

By mid-December he’d sewn up $9.4 million from nine dif- 
ferent big money managers.* Six months later he’d raise $15 mil- 
lion from four new investors. The money Brad needed that he 
didn’t get he kicked in himself: By January 1, 2013, he’d put his 
life savings on the line. 

At the same time, he went looking for people: software devel- 
opers and hardware engineers and network engineers to build 
the system, the operations people to run it, and the salespeople 
to explain it to Wall Street. He had no trouble attracting people 
who knew him — -just the opposite. A shockingly large number 
of people he’d worked with at RBC apparently felt the urge to 
entrust him with their careers. Several dozen people had hinted 
that they’d like to join him and do whatever he was doing. He 
found himself in a series of bizarre conversations, in which he 
tried to explain why they were better off being paid hundreds of 
thousands of dollars a year to work at a big Wall Street bank than 
taking a flier on a new business that had neither a clear plan nor 
a penny of financing. Still, people followed. Allen Zhang, the 
Golden Goose himself, got fired for sending RBC’s computer 
code to himself and instantly turned up at Brad’s front door. 
Billy Zhao was made redundant after he automated a compli- 

* The first round of investors included Greenlight Capital, Capital Group, Brandes 
Investment Partners, Senator Investment Group, Scoggin Capital Management, Belfer 
Management, Pershing Square, and Third Point Partners. 



cated task so well that the bank no longer needed his help to do 
it: He came on board, too. But Brad needed people who didn’t 
know him, and who knew things he did not know. He needed, 
especially, people with a deep understanding of high-frequency 
trading and stock exchanges. And the first person he found was 
Don Bollerman. 

WHAT EVERYONE NOTICED about Don Bollerman — even if they 
didn’t quite put it this way — was how badly he wanted not to be 
surprised by his own life. On top of that, he’d grown up in the 
Bronx and carried with him a resistance to sentiment. He ripped 
the filters off cigarettes before he smoked them. He weighed 
a hundred pounds more than he should and ignored entreat- 
ies from his colleagues to exercise or take care of himself. “I’m 
gonna die young anyway,” he’d say. His finer feelings he treated 
much the way he treated his body, with something approaching 
disdain. “Much is made of a kind heart,” he said. “I’m more of a 
feed-yourself-or-die kind of guy.” 

To eliminate the possibility of surprise required not that 
Don’s life be especially unsurprising but that he control his feel- 
ings about whatever surprise it produced. How much he wished 
to manage these emotions could be seen when they were at 
their least manageable. On September 11, 2001, Don worked 
at a small new electronic stock exchange on the twelfth floor 
of 100 Broadway, five hundred yards from the World Trade 
Center. He’d arrived at seven that morning. Before the stock 
market opened, he heard a bump, which sounded as if it had 
come from upstairs. “What we thought is that it was guys mov- 
ing heavy equipment,” he said. “Five minutes later it’s snowing 
office memos.” He and his colleagues went to the window and 



heard the news on the office TV about the plane hitting one 
of the towers. “I thought it was an attack right away,” he said, 
and so he was less shocked than his colleagues by what hap- 
pened next. They had a direct view of the Twin Towers, across 
the Trinity Church graveyard, over the top of the American 
Stock Exchange. The second plane hit. “I felt the heat on my 
face through the window. You open the barbecue and your face 
feels like it pulls back — that feeling,” he said. They discussed 
whether the towers were tall enough to reach them if one fell 
over. Then the first tower fell. “That’s when we ran for the 
staircase.” By the time they got to the sixth floor, Don couldn’t 
see his hands in front of his face. Once outside, in the blizzard, 
he headed east. He walked alone and matter-of-factly up Third 
Avenue and then across the bridge over the Harlem River to his 
apartment in the Bronx, sixteen miles in all. What stuck out in 
his mind from the day was how, when he arrived in Harlem, 
some women were waiting outside their homes with fruit juice 
for him to drink. “That one caught in my throat,” he said. He 
added quickly, “Actually, I feel like a bit of a pussy, that it got to 
me that way.” 

The attack, and the ensuing market convulsions, killed off 
the new electronic stock exchange that employed him. Don, 
who had thought that the business was probably going to die 
anyway, went back to NYU to finish his college degree, and 
then on to a career at the Nasdaq stock exchange. Seven years 
in, his job was to deal with everything that happened after a 
trade occurred, but his specific role was less important than 
his general understanding — both Ronan and Schwab thought 
that Don Bollerman knew breathtakingly more about the inner 
workings of the stock exchanges than anyone they had ever met. 
He’d been privy to just about everything that happened inside 



Nasdaq, and brought an understanding not just of what had 
gone wrong but how it might be set right. 

What had gone wrong, in Don’s view, wasn’t all that surpris- 
ing or complicated. It had to do with human nature, and the 
power of incentives. The rise of high-frequency trading — and 
its ability to gain an edge on the rest of the market — had cre- 
ated an opportunity for new exchanges, like BATS and Direct 
Edge. By giving HFT what it wanted (speed, in relation to the 
rest of the market; complexity only HFT understood; and pay- 
ment to brokers for their customers’ orders, so that HFT had 
something to trade against), the new stock exchanges had stolen 
market share from the old stock exchanges. Don couldn’t speak 
for NYSE, but he had watched Nasdaq respond by giving HFT 
firms what they asked for — and then figuring out how to charge 
them for it. “It was almost like you couldn’t do anything about 
it,” he said. “We did all this speed, and I don’t think we fully 
understood what it was being used for. We just thought, The 
new rules caused people to have a new experience and then 
new wants and needs.” Nasdaq had become a public company in 
2005, a year after Don had joined it. It had earnings targets to 
hit; it was incentivized to make decisions, and to make changes 
in the nature of the exchange, with a focus on their short-term 
consequences. “It’s hard to be forward-thinking when the whole 
of corporate America is about the next quarter’s earnings,” said 
Don. “It went from ‘Is this good for the market?’ to ‘Is this bad 
for the market?’ And then it slides to: ‘Can we get this through 
the SEC?’ The demon in this part of the story is expediency.” 
By late 2011, when Bollerman quit his job (“I felt there was a 
lack of leadership”), more than two-thirds of Nasdaq’s revenues 
derived, one way or another, from high-frequency trading firms. 

Don wasn’t shocked or even all that disturbed by what had 



happened, or, if he was, he disguised his feelings. The facts of 
Wall Street life were inherently brutal, in his view. There was 
nothing that he couldn’t imagine someone on Wall Street doing. 
He was fully aware that the high-lrequency traders were prey- 
ing on investors, and that the exchanges and brokers were being 
paid to help them to do it. He refused to feel morally outraged 
or self-righteous about any of it. “I would ask the question, ‘On 
the savannah, are the hyenas and the vultures the bad guys?’ ” he 
said. “We have a boom in carcasses on the savannah. So what? 
It’s not their fault. The opportunity is there.” To Don’s way 
of thinking, you were never going to change human nature — 
though you might alter the environment in which it expressed 
itself. Or maybe that’s just what Don wanted to believe. “He’s 
kind of like the mob guy who cries every now and then after a 
hit,” said Brad, who thought that Don was exactly the sort of 
person he needed. Brad wasn’t in the market for self-righteous- 
ness, or for people who defined themselves by their fine moral 
sentiment. “Disillusion isn’t a useful emotion,” he said. “I need 
soldiers.” Don was a soldier. 

THEIR NEW EXCHANGE needed a name. They called it the Investors 
Exchange, which wound up being shortened to IEX.* Its goal 
was not to exterminate the hyenas and the vultures but, more 
subtly, to eliminate the opportunity for the kill. To do that, 
they needed to figure out the ways that the financial ecosystem 
favored predators over their prey. Enter the Puzzle Masters. 

* In the interest of clarity, they d hoped to preserve the full name, but they discovered 
a problem doing so when they set out to create an Internet address: investorsexchange. 
com. To avoid that confusion, they created another. 



Back in 2008, when it had first occurred to Brad that the stock 
market had become a black box whose inner workings eluded 
ordinary human understanding, he’d gone looking for techno- 
logically gifted people who might help him open the box and 
understand its contents. He’d started with Rob Park; with less 
precision, he gathered others. One was a twenty-year-old Stan- 
ford junior named Dan Aisen, whose resume Brad discovered in 
a pile at RBC. The line that leapt out at him was “Winner of 
the Microsoft College Puzzle Challenge.” Every year, Microsoft 
sponsored this one-day, ten-hour national brain-twisting mara- 
thon. It attracted thousands of young math and computer science 
types. Aisen and three friends had competed, in 2007, against 
one thousand other teams and had won the whole thing. “It’s 
kind of a mix of cryptography, ciphers, and Sudoku,” explained 
Aisen. The solution to each puzzle offered clues to the other 
puzzles; to be really good at it, a person needed not only tech- 
nical skill but exceptional pattern recognition. “There’s some 
element of mechanical work, and some element of ‘aha!’” said 
Aisen. Brad had given Aisen both a job and a nickname, the 
Puzzle Master, soon shortened, by RBC’s traders, to Puz. Puz 
was one of the people who had helped him create Thor. 

Puz’s peculiar ability to solve puzzles was suddenly even more 
relevant. Creating a new stock exchange is a bit like creating 
a casino: Its creator needs to ensure that the casino cannot in 
some way be exploitable by the patrons. Or, at worst, he needs 
to know exactly how his system might be exploited, so that 
he might monitor the exploitation — as a casino monitors card 
counting at the blackjack tables. “You are designing a system,” 
said Puz, “and you don’t want the system to be gameable.” The 
trouble with the stock market — with all of the public and private 
exchanges — was that they were fantastically gameable, and had 



been gamed: first by clever guys in small shops and then by prop 
traders at the big Wall Street banks. That was the problem, Puz 
thought. From the point of view of the most sophisticated trad- 
ers, the stock market wasn’t a mechanism for channeling capital 
to productive enterprise but a puzzle to be solved. “Investing 
shouldn’t be about gaming a system,” he said. “It should be 
about something else.” 

The simplest way to design a stock exchange that could not 
be gamed was to hire the very people best able to game it, and 
encourage them to take their best shots. Brad didn’t know any 
other national puzzle champions, but Puz did. The first per- 
son he mentioned was his former Stanford teammate Francis 
Chung. Francis worked as a trader at a high-frequency trading 
firm but didn’t like his job. Brad invited him in for a job inter- 
view. Francis turned up — and just sat there. 

Brad gazed across a table: The young man was round-faced 
and shy and sweet-natured but essentially noninteractive. 

“Why are you good at solving puzzles?” Brad asked him. 
Francis thought about it a moment. 

“I’m not sure how good I am,” said Francis. 

“You just won the national puzzle-solving championship!” 

Francis thought about that some more. 

“Yeah, I guess,” he said. 

Brad had done a lot of these interviews with technologists 
whose skills he could not judge. He left it to Rob to figure out 
if they could actually write code. He just wanted to know what 
kind of people they were. “I’m just looking for the type of peo- 
ple who won’t get along here,” said Brad. “Typically, it’s because 
the way they describe their experience, and the things they say, 
are very self-serving. ‘I don’t get enough credit for what I do,’ or 
I’m overlooked.’ It’s all about me. They’re obsessed with titles 



and other things that don’t matter. I try to find out how they 
work with other people. If they don’t know something, what do 
they do? I look for sponges, learners.” With Francis he had no 
idea. Every question elicited some choked reply. Desperate to get 
something, anything, out of him, Brad finally asked, “All right, 
just tell me: What do you like to do?” Francis thought about it. 

“I like to dance,” he said. Then he went completely silent. 

After Francis had left, Brad hunted down Puz. “Are you sure 
this is the guy?” he asked. 

“Trust me,” said Puz. 

It took roughly six weeks for Francis to get comfortable 
enough to speak up. Once he did, he wouldn’t shut up. It was 
Francis who would eventually take all the rules they created for 
the exchange and translate them into step-by-step instructions 
for a computer to follow. Francis alone had the entire logic of 
the new exchange in his head. Francis fought more than anyone 
for, as he put it, “making the system so simple there is nothing 
to game.” And it was Francis whom Bollerman dubbed The 
Spoiler, because every time the other guys thought they had 
figured something out, Francis would step in and show them 
some loophole in their logic. “The level to which the kid will 
worry a problem is what really separates him,” said Don Boiler- 
man, “without any prior concern for whose theory he’s going to 
upset — including his own.” 

The only problem with the Puzzle Masters was that neither 
of them had ever worked inside a stock exchange. Bollerman 
brought in a guy from Nasdaq, Constantine Sokoloff, who had 
helped to build the exchange’s matching engine. “The Puzzle 
Masters needed a guide, and Constantine was that guide,” said 
Brad. Constantine was also Russian, born and raised in a small 
town on the Volga River. He had a theory about why so many 



Russians had wound up inside high-frequency trading. The 
old Soviet educational system channeled people away from the 
humanities and into math and science. The old Soviet culture 
also left its former citizens oddly prepared for Wall Street in 
the early twenty-first century. The Soviet-controlled economy 
was horrible and complicated but riddled with loopholes. Every- 
thing was scarce; everything was also gettable, if you knew how 
to get it. “We had this system for seventy years,” said Constan- 
tine. “People learn to work around the system. The more you 
cultivate a class of people who know how to work around the 
system, the more people you will have who know how to do it 
well. All of the Soviet Union for seventy years were people who 
are skilled at working around the system.” The population was 
thus well suited to exploit megatrends in both computers and the 
United States financial markets. After the fall of the Berlin Wall, 
a lot of Russians fled to the United States without a lot of Eng- 
lish; one way to make a living without having to converse with 
the locals was to program their computers. “1 know people who 
never programmed computers but when they get here they say 
they are computer programmers,” said Constantine. A Russian 
also tended to be quicker than most to see holes built into the 
U.S. stock exchanges, even if those holes were unintentional, 
because he had been raised by parents, in turn raised by their 
own parents, to game a flawed system. 

The role of the Puzzle Masters was to ensure that the new 
stock exchange did not contain aspects of a puzzle. That it had 
no problem inside its gears that could be “solved.” To begin, they 
listed the features of the existing stock exchanges and picked 
them apart. Aspects of the existing stock exchanges obviously 
incentivized bad behavior. Rebates, for instance: The maker- 
taker system of fees and kickbacks used by all of the exchanges 



was simply a method for paying the big Wall Street banks to 
screw the investors whose interests they were meant to guard. 
The rebates were the bait in the high-frequency traders’ flash 
traps. The moving parts of the traps were order types. Order 
types — like “market” and “limit” — exist so that the person 
who submits the order to buy or sell stock retains some control 
over his order after it has entered the marketplace.* They are an 
acknowledgment that the investor cannot be physically present 
on the exchange to micromanage his situation. Order types also 
exist, less obviously, so that the person who is buying or selling 
stock can embed, in a single simple instruction, a lot of other, 
smaller instructions. 

The old order types were simple and straightforward and mainly 
sensible. The new order types that accompanied the explosion of 
high-frequency trading were nothing like them, either in detail 
or spirit. When, in the summer of 2012, the Puzzle Masters gath- 
ered with Brad and Don and Ronan and Rob and Schwall in a 
room to think about them, there were maybe one hundred fifty 

* The market order is the first and simplest type. Say, for instance, an investor wishes to 
buy 100 shares of Procter & Gamble. When he submits his order, the market for the shares 
in P&G is, say, 80-80.02. If he submits a market order, he will pay the offering price — in 
this case, $80.02 per share. But a market order comes with a risk: that the market will 
move between the time the order is submitted and the time it reaches the market. The 
flash crash was a dramatic illustration of that risk: Investors who submitted market orders 
wound up paying $100,000 a share for P&G and selling those same shares for a penny 
apiece. To control the risk of a market order, a second order type was invented, the limit 
order. The buyer of P&G shares might say, for instance: “I’ll buy a hundred shares, with 
a limit of eighty dollars and three cents a share.” By doing so, he will ensure that he does 
not pay $100,000 a share; but this may lead to a missed opportunity — he may not buy the 
shares at all, because he never gets the price he wanted. Another simple, and long-used, 
order type is “good ’til canceled.” The investor who says he wants to buy 100 shares of 
P&G at $80 a share, “good ’til canceled,” will never have to think about it again until 
he buys them, or does not. 



different order types. What purpose did each serve? How might 
each be used? The New York Stock Exchange had created an order 
type that ensured that the trader who used it would trade only if 
the order on the other side of his was smaller than his own order; 
the purpose seemed to be to prevent a high-frequency trader from 
buying a small number of shares from an investor who was about 
to crush the market with a huge sale. Direct Edge created an 
order type that, for even more complicated reasons, allowed the 
high-frequency trading firm to withdraw 50 percent of its order 
the instant someone tried to act on it. All of the exchanges offered 
something called a Post-Only order. A Post-Only order to buy 
100 shares of Procter & Gamble at $80 a share says, “I want to buy 
a hundred shares of Procter & Gamble at eighty dollars a share, 
but only if I am on the passive side of the trade, where I can collect 
a rebate from the exchange.” As if that weren’t squirrely enough, 
the Post-Only order type now had many even more dubious per- 
mutations. The Hide Not Slide order, for instance. With a Hide 
Not Slide order, a high-frequency trader — for who else could or 
would use such a thing? — would say, for example, “I want to buy 
a hundred shares of P&G at a limit of eighty dollars and three 
cents a share, Post-Only, Hide Not Slide.” 

One of the joys of the Puzzle Masters was their ability to 
figure out what on earth that meant. The descriptions of single 
order types filed with the SEC often went on for twenty pages, 
and were in themselves puzzles — written in a language barely 
resembling English and seemingly designed to bewilder anyone 
who dared to read them. “I considered myself a somewhat expert 
on market structure,” said Brad. “But I needed a Puzzle Master 
with me to fully understand what the fuck any of it means.” 

A Hide Not Slide order — it was just one of maybe fifty such 
problems the Puzzle Masters solved — worked as follows: The 



trader said he was willing to buy the shares at a price ($80.03) 
above the current offering price ($80.02), but only if he was on 
the passive side of the trade, where he would be paid a rebate. 
He did this not because he wanted to buy the shares. He did 
this in case an actual buyer of stock — a real investor, channeling 
capital to productive enterprise — came along and bought all 
the shares offered at $80.02. The high-frequency trader’s Hide 
Not Slide order then established him as first in line to purchase 
P&G shares if a subsequent investor came into the market to 
sell those shares. This was the case even if the investor who 
had bought the shares at $80.02 expressed further demand for 
them at the higher price. A Hide Not Slide order was a way for 
a high-frequency trader to cut in line, ahead of the people who’d 
created the line in the first place, and take the kickbacks paid to 
whoever happened to be at the front of the line. 

The Puzzle Masters spent days working through the many 
order types. All of them had one thing in common: They were 
designed to create an edge for HFT at the expense of investors. 
“We’d always ask, ‘What is the point of that order, if you want 
to trade?’ ” said Brad. “Most of the order types were designed to 
not trade, or at least to discourage trading. [With] every rock we 
turned over, we found a disadvantage for the person who was 
actually there to trade.” Their purpose was to hardwire into the 
exchange’s brain the interests of high-frequency traders — at the 
expense of everyone who wasn’t a high-frequency trader. And 
the high-frequency traders wanted to obtain information, as 
cheaply and risklessly as possible, about the behavior and inten- 
tions of stock market investors. That is why, though they made 
only half of all trades in the U.S. stock market, they submitted 
more than 99 percent of the orders: Their orders were a tool 
for divining information about ordinary investors. “The Puzzle 



Masters showed me the length the exchanges were willing to go 
to — to satisfy a goal that wasn’t theirs,” said Brad. 

The Puzzle Masters might not have thought of it this way at 
first, but in trying to design their exchange so that investors who 
came to it would remain safe from high-frequency traders, they 
were also divining the ways in which high-frequency traders 
stalked their prey. As they worked through the order types, they 
created a taxonomy of predatory behavior in the stock market. 
Broadly speaking, it appeared as if there were three activities 
that led to a vast amount of grotesquely unfair trading. The first 
they called “electronic front-running” — seeing an investor try- 
ing to do something in one place and racing him to the next. 
(What had happened to Brad, when he traded at RBC.) The 
second they called “rebate arbitrage” — using the new complexity 
to game the seizing of whatever kickbacks the exchange offered 
without actually providing the liquidity that the kickback was 
presumably meant to entice. The third, and probably by far 
the most widespread, they called “slow market arbitrage.” This 
occurred when a high-frequency trader was able to see the price 
of a stock change on one exchange, and pick off orders sitting on 
other exchanges, before the exchanges were able to react. Say, for 
instance, the market for P&G shares is 80-80.01, and buyers and 
sellers sit on both sides on all of the exchanges. A big seller comes 
in on the NYSE and knocks the price down to 79.98—79.99. 
High-frequency traders buy on NYSE at $79.99 and sell on all 
the other exchanges at $80, before the market officially changes. 
This happened all day, every day, and generated more billions of 
dollars a year than the other strategies combined. 

All three predatory strategies depended on speed, and to 
speed the Puzzle Masters turned their attention, once they were 
done with the order types. They were trying to create a safe 



place, where every dollar stood the same chance. How to do 
that, when a handful of people in the market would always be 
faster than everyone else? They couldn’t very well prohibit high- 
frequency traders from trading on the exchange— an exchange 
needed to offer fair access to all broker-dealers. And, anyway, it 
wasn’t high-frequency trading in itself that was pernicious; it was 
its predations. It wasn’t necessary to eliminate high-frequency 
traders; all that was needed was to eliminate the unfair advan- 
tages they had, gained by speed and complexity. Rob Park put it 
best: “Let’s say you know something before everyone else. You 
are in a privileged state. Eliminating the position of privilege is 
impossible — some people always will get the information first. 
Some people will always get it last. You can’t stop it. What you 
can control is how many moves they can make to monetize it.” 

The obvious starting point was to prohibit high-frequency 
traders from doing what they had done on all the other 
exchanges — co-locating inside them, and getting the informa- 
tion about whatever happened on those exchanges before every- 
one else.* That helped, but it did not entirely solve the problem: 
High-frequency traders would always be faster at processing the 
information they acquired from any exchange, and they would 
always be faster than anyone else to exploit that information on 

* The value of the microseconds saved by proximity to the exchanges explained why the 
exchanges expanded, bizarrely, after the people inside them had vanished. You might 
have thought that, when the whole of the stock market moved from a floor that needed 
to accommodate thousands of human traders into a single black box, the building that 
housed the exchange might shrink. Think again. The old New York Stock Exchange 
building on the corner of Wall and Broad streets was 46,000 square feet. The NYSE 
data center in Mahwah, which housed the exchange, was 400,000 square feet. Because 
the value of the space around the black box was so great, the exchanges expanded to 
enclose greater amounts of that space so that they might sell it. IEX could function hap- 
pily inside a space roughly the size of a playhouse. 



other exchanges. This new exchange would be required both 
to execute trades on itself and to route, to the other exchanges, 
the orders it was unable to execute. The Puzzle Masters wanted 
to encourage big orders, and larger-sized trades, so that honest 
investors with a lot of stock to sell might collide with honest 
investors who had a lot of stock to buy, without the intercession 
of HFT. If some big pension fund came to IEX to buy a million 
shares of P&G and found only 100,000 for sale there, it would 
be exposed to some high-frequency trader figuring out that its 
demand for P&G shares was unsatisfied. The Puzzle Masters 
wanted to be sure that they could beat any HFT firm to the sup- 
ply of P&G stock on the other exchanges. 

They entertained all sorts of ideas about how to solve the 
speed problem. “We had professors coming through here con- 
stantly,” said Brad. For instance, one professor suggested a 
“randomized delay.” Every order submitted to the new stock 
exchange would be assigned, at random, some time lag before 
it entered the market. The market information some high-fre- 
quency trader obtained with his 100-share sell order, the sole 
intention of which was to uncover the existence of a big buyer, 
might thus move so slowly that it would prove of no use to him. 
An order would become, like a lottery ticket, a matter of chance. 
The Puzzle Masters instantly spotted the problem: Any decent 
HFT firm would simply buy huge numbers of lottery tickets — 
to increase its chances of being the 100-share sell order that 
collided with the massive buy order. “Someone will just flood 
the market with orders,” said Francis. “You end up massively 
increasing quote traffic for every move.” 

It was Brad who had the crude first idea: Everyone is fighting 
to get in as close to the exchange as possible. Why not push them as far 
away as possible? Put ourselves at a distance, but don’t let anyone else be 



there. In designing the exchange, they needed to consider what 
the regulators would tolerate; they couldn’t just do whatever they 
wanted. Brad kept a close eye on what the regulators already had 
approved, and paid special attention when the New York Stock 
Exchange won the SEC’s approval for the strange thing they 
had done in Mahwah. They’d built this 400,000-square-foot 
fortress in the middle of nowhere, and they planned to sell, to 
high-frequency traders, access to their matching engine. But 
the moment they announced their plans, high-frequency trad- 
ing firms began to buy up land surrounding the fort — so that 
they might be near the NYSE matching engine, without paying 
the NYSE for the privilege. In response, the NYSE somehow 
persuaded the SEC to let them make a rule for themselves: Any 
banks or brokers or HFT firms that did not buy (expensive) 
space inside the fort would be allowed to connect to the NYSE 
in one of two places: Newark, New Jersey, or Manhattan. The 
time required to move a signal from those places to Mahwah 
undermined EIFT strategies; and so the banks and brokers and 
HFT firms were all forced to buy space inside the fort from 
the NYSE. Brad thought: Why not create the distance that under- 
mines HFT’s strategies, without selling high-frequency traders the right 
to put their computers in the same building? “There was a precedent: 
They’d let NYSE do it,” Brad said. “Unless the regulators said, 
‘You must allow co-location,’ ” they’d have to let IEX forbid it. 

The idea was to establish the IEX computer that matched 
buyers and sellers (the matching engine) at some meaningful 
distance from the place traders connected to IEX (called the 
“point of presence”), and to require anyone who wanted to 
trade to connect to the exchange at that point of presence. If 
you placed every participant in the market far enough away 
from the exchange, you could eliminate most, and maybe all, 



of the advantages created by speed. Their matching engine, 
they already knew, would be located in Weehawken, New Jer- 
sey (they’d been offered cheap space in a data center). The only 
question was: Where to put the point of presence? “Let’s put 
it in Nebraska,” someone said, but they all knew it would be 
harder to get the already reluctant Wall Street banks to connect 
to their market if the banks had to send people to Omaha to do 
it. Actually, though, it wasn’t necessary for anyone to move to 
Nebraska. The delay needed only to be long enough for IEX, 
once it had executed some part of a customer’s buy order, to beat 
HFT in a race to any other shares available in the marketplace at 
the same price — that is, to prevent electronic front-running. It 
needed to be long enough, also, for IEX, each time a share price 
moved on any exchange, to process the change, and to move the 
prices of any orders resting on it, so that they didn’t get picked 
off — in the way, say, that Rich Gates had been picked off, when 
he ran his tests to determine if he was being ripped off inside the 
dark pools run by the big Wall Street banks. (That is, to prevent 
“slow market arbitrage.”) The necessary delay turned out to be 
320 microseconds; that was the time it took them, in the worst 
case, to send a signal to the exchange farthest from them, the 
NYSE in Mahwah. Just to be sure, they rounded it up to 350 

The new stock exchange also cut off the food source for all 
identifiable predators. Brad, when he was a trader, had been 
cheated because his orders had arrived first at BATS, where 
HFT guys had picked up his signal and raced him to the other 
exchanges. The fiber routes through New Jersey that Ronan 
handpicked were chosen so that an order sent from IEX to the 
other exchanges arrived at them all at precisely the same time. 
(He thus achieved with hardware what Thor had achieved with 



software.) Rich Gates had gotten himself picked off in the Wall 
Street dark pools because the dark pools had not moved fast 
enough to re-price his order. The slow movement of the dark 
pools’ prices had made it possible for a high-frequency trader (or 
the Wall Street banks’ own traders) to exploit the orders inside 
it — legally. To prevent the same thing from happening on their 
new exchange, IEX needed to be extremely fast — much faster 
than any other exchange. (At the same time that they were slow- 
ing down everyone who traded on their exchange, they were 
speeding themselves up.) To “see” the prices on the other stock 
exchanges, IEX didn’t use the SIP or some phony improvement 
on the SIP but instead created their own private, HFT-like pic- 
tures of the entire stock market. Ronan had scoured New Jersey 
for paths from their computers in Weehawken to all the other 
exchanges; there turned out to be thousands of them. “We used 
the fastest subterranean routes,” said Ronan. “All the fiber we 
used was created by EIFT for HFT. One hundred percent of it.” 
The 350-microsecond delay worked like a head start in a foot- 
race. It ensured that IEX would be faster to see and react to the 
wider market than even the fastest high-frequency trader, thus 
preventing investors’ orders from being abused by changes in that 
market. In the bargain, it prevented high-frequency traders — 
who would inevitably try to put their computers nearer than 
everyone else’s to IEX’s in Weehawken — from submitting their 
orders onto IEX more quickly than everyone else. 

To create the 350-microsecond delay, they needed to keep 
the new exchange roughly thirty-eight miles from the place the 
brokers were allowed to connect to the exchange. That was a 
problem. Having cut one very good deal to put the exchange in 
Weehawken, they were offered another: to establish the point of 
presence in a data center in Secaucus, New Jersey. The two data 



centers were less than ten miles apart, and already populated 
by other stock exchanges and all the high-frequency traders. 
(“Were going into the lion’s den,” said Ronan.) A bright idea 
came from a new employee, James Cape, who had just joined 
them from an HFT firm: Coil the fiber. Instead ot running straight 
fiber between the two places, coil thirty-eight miles of fiber 
and stick it in a compartment the size of a shoebox to simulate 
the effects of the distance. And that’s what they did. The infor- 
mation flowing between IEX and all the players on it would 
thus go round and round, in thousands of tiny circles, inside the 
magic shoebox. From the high-frequency traders’ point of view, 
it was as if they’d been banished to West Babylon, New York. 

Creating fairness was remarkably simple. They would not sell 
to any one trader or investor the right to put his computers next 
to the exchange, or special access to data from the exchange. 
They would pay no kickbacks to brokers or banks that sent orders; 
instead, they’d charge both sides of any trade the same amount: 
nine one-hundredths of a cent per share (known as 9 “mils”). 
They’d allow just three order types: market, limit, and Mid- Point 
Peg, which meant that the investor’s order rested in between the 
current bid and offer of any stock. If the shares of Procter & Gam- 
ble were quoted in the wider market at 80-80.02 (you can buy at 
$80.02 or sell at $80), a Mid-Point Peg order would trade only at 
$80.01. “It’s kind of like the fair price,” said Brad. 

Finally, to ensure that their own incentives remained as closely 
aligned as they could be with those of stock market investors, the 
new exchange did not allow anyone who could trade directly on 
it to own any piece of it: Its owners were all ordinary investors 
who needed first to hand their orders to brokers. 

The design of the new stock exchange was such that it would 
yield all sorts of new information about the inner workings of 



the U.S. stock market — and, indeed, the entire financial system. 
For instance, it did not ban but welcomed high-frequency trad- 
ers who wished to trade on it. It high-frequency traders per- 
formed a valuable service in the financial markets, they should 
still do so, after their unfair advantages had been eliminated. 
Once the new stock exchange opened for business, IEX would 
be able to see how much of what HFT did was useful simply by 
watching what, it anything, high-frequency traders did on the 
new exchange, where predation was not possible. The Puzzle 
Masters’ only question was whether, in their design, they had 
accounted for every possible form of market predation. That was 
the one thing even they did not know: whether they had missed 

THE HIDDEN PASSAGES and trapdoors that riddled the exchanges 
enabled a handlul ot players to exploit everyone else; the latter 
didn’t understand that the game had been designed precisely for 
the former. As Brad put it, “It’s like you run this casino, and you 
need to get players in to attract other players. You invite a few 
players in to start a game of Texas Flold’em by telling them that 
the deck doesn’t have any jacks or queens in it, and that you won’t 
tell the other people who come to play with them. Flow do you 
get people into the casino? You pay the brokers to bring them 
there.” By the summer of 2013, the world’s financial markets 
were designed to maximize the number of collisions between 
ordinary investors and high-frequency traders — at the expense 
of ordinary investors, and for the benef it of high-frequency trad- 
ers, exchanges, Wall Street banks, and online brokerage firms. 
Around those collisions an entire ecosystem had arisen. 

Brad had heard many firsthand accounts about the nature 



of that ecosystem. One came from a man named Chris Nagy, 
who, until 2012, had been responsible for selling the order flow 
for TD Ameritrade. Every year, people from banks and high- 
frequency trading firms would fly to Omaha, where TD Ameri- 
trade was based, and negotiate with Nagy. “Most of the deals 
tend to be handshake deals,” Nagy said. “You go out to a steak 
dinner. ‘We’ll pay you two cents a share. Everything is good.’” 
The negotiations were always done face-to-face, because no one 
involved wanted to leave a paper trail. “The payment for the 
order flow is as off-the-record as possible,” said Nagy. “They 
never have an email or even a phone call. You had to fly down 
to meet with us.” For its part, TD Ameritrade was required to 
publish how much per share they were making from the prac- 
tice but not the total amounts, which were buried on its income 
statements on a line labeled “Other Revenue.” “So you can see 
the income, but you can’t see the deals.” 

In his years selling order flow, Nagy noticed a couple of 
things — and he related them both to Brad and his team when 
he came to visit them to find out why he kept hearing about 
this strange new thing called IEX. The first was that the mar- 
ket complexity created by Reg NMS — the rapid growth in the 
number of stock markets, and in high-frequency trading — raised 
the value of a stock market customer’s order. “It caused the value 
of our flow to triple, a least,” Nagy said. The other thing he 
couldn’t help but notice was that not all of the online brokers 
appreciated the value of what they were selling. TD Ameri- 
trade was able to sell the right to execute its customers’ orders 
to high-frequency trading firms for hundreds of millions a year. 
The bigger Charles Schwab, whose order flow was even more 
valuable than TD Ameritrade’s, had sold its flow to UBS back 
in 2005, in an eight-year deal, for only $285 million. (UBS 



charged the high-frequency trading firm Citadel some undis- 
closed sum to execute Schwab’s trades.) “Schwab left at least a 
billion dollars on the table,” Nagy said. A lot of the people sell- 
ing their customers’ orders, it seemed to Nagy, had no idea of 
the value of the information the orders contained. Even he was 
unsure; the only way to know would be to find out how much 
money high-frequency traders were making by trading against 
slow-footed individual investors. “I’ve tried over the years [to 
find out how much money was being made by high-frequency 
trading],” Nagy said. “The market makers are always reluctant 
to share their performance.” What Nagy did know was that the 
simple retail stock market order was, from the point of view of 
high-frequency traders, easy kill. “Whose order flow is the most 
valuable?” he said. “Yours and mine. We don’t have black boxes. 
We don’t have algos. Our quotes are late to the market — a full 
second behind.”* 

High-frequency traders sought to trade as often as possible 
with ordinary investors, who had slower connections. They 
were able to do so because the investors themselves had only the 
faintest clue of what was happening to them, and also because 
the investors, even big, sophisticated ones, had no ability to con- 
trol their own orders. When, say, Fidelity Investments sent a big 
stock market order to Bank of America, Bank of America treated 
that order as its own — and behaved as if it, not Fidelity, owned 
the information associated with that order. The same was true 

* In 2008, Citadel bought a stake in the online broker E*Trade, which was flounder- 
ing in the credit crisis. The deal stipulated that E*Trade route some percentage of its 
customers’ orders to Citadel. At the same time, E*Trade created its own high-frequency 
trading division, eventually called G1 Execution Services, to exploit the value of those 
orders for itself. Citadel’s founder and CEO, Kenneth Griffin, pitched a fit, and called 
out E*Trade publicly for failing to execute its customers’ orders properly. 



when an individual investor bought stock through an online 
broker. The moment he pressed the Buy icon on his screen, the 
business was out of his hands, and the information about his 
intentions belonged, in effect, to E*Trade, or TD Ameritrade 
or Schwab. 

But the role in this of the nine big Wall Street banks that 
controlled 70 percent of all stock market orders was more com- 
plicated than the role played by TD Ameritrade. The Wall Street 
banks controlled not only the orders, and the informational value 
of those orders, but dark pools in which those orders might be 
executed. The banks took different approaches to milking the 
value of their customers’ orders. All of them tended to send the 
orders first to their own dark pools before routing them out to 
the wider market. Inside the dark pool, the bank could trade 
against the orders themselves; or they could sell special access to 
the dark pool to high-frequency traders. Either way, the value 
of the customers’ orders was monetized — by the big Wall Street 
bank, for the big Wall Street bank. If the bank was unable to 
execute a stock market order in its own dark pool, the bank 
directed that order first to the exchange that paid the biggest 
kickback for it — when the kickback was simply the bait for some 
flash trap. 

It the Puzzle Masters were right, and the design of IEX elimi- 
nated the advantage of speed, IEX would reduce the value of 
investors’ stock market orders to zero. If the orders couldn’t be 
exploited on this new exchange — if the information they con- 
tained was worthless — who would pay for the right to execute 
them? The big Wall Street banks and online brokers charged by 
investors with routing stock market orders to IEX would sur- 
render billions of dollars in revenues in the process. And that, as 
everyone involved understood, wouldn’t happen without a fight. 



One afternoon during the summer of 2013, a few months 
before the exchange planned to open for business, Brad called 
a meeting to figure out how to make the big Wall Street banks 
feel watched. IEX had raised more capital and hired more peo- 
ple and moved to a bigger room, on the thirtieth floor of 7 
World Trade Center. There still was no separate place to meet, 
however, so they gathered in a corner of the big room, where a 
whiteboard met a window that offered a spectacular view of the 
9/11 memorial. Don leaned with his back against the window, 
along with Ronan, Schwall, and Rob Park, while Brad stood in 
front of the whiteboard and took a whiteboard marker out of a 
bin. The twenty or so other employees of IEX remained at their 
desks in the room, pretending that nothing was happening. 

Then Matt Trudeau appeared and joined in. Matt was the 
only person in the room who had ever opened a brand-new 
stock exchange, and so he tended to be included in every busi- 
ness discussion. Oddly enough, among them he was least, by 
nature, a businessman. He’d entered college to major in painting 
and then, deciding he lacked the talent to make it as a painter, 
and thinking he might make it as an academic, had moved into 
the anthropology department. He didn’t become an anthropolo- 
gist, either. Atter college he’d found work adjusting auto insur- 
ance claims — a job he judged to be among the world’s most 
soul-sucking. One day on a lunch break, he noticed a televi- 
sion switched on to CNBC and wondered, “Why are there two 
separate ticker tapes?” He began to study the stock market. Five 
years later, in the mid-2000s, he was opening new, American- 
style stock exchanges in foreign countries for a company with the 
mystifying name Chi-X Global. (“It was marketing gone awry,” 
he said. “We spent the first fifteen minutes of every meeting try- 
ing to explain our name.”) He’d been one part businessman and 



one part missionary: He met with officials of various govern- 
ments, wrote white papers, and sat on panels to extol the virtues 
of American financial markets. After opening Chi-X Canada, 
he’d advised firms trying to open stock exchanges in Singapore, 
Tokyo, Australia, Hong Kong, and London. “Did I think I was 
doing God’s work?” he said later. “No. But I did think market 
efficiency was something important for the economy.” 

As he spread the American financial gospel, he couldn’t help 
but notice a pattern: A new exchange would open, and nothing 
would happen on it — until the high-frequency traders showed 
up, stuck their computers beside the exchange’s matching 
engine, and turned the exchange around. Then he began to hear 
things — that some of the HFT guys might be shady, that stock 
exchanges had glitches built into them that HFT could use to 
exploit ordinary investors. He couldn’t point to specific wrong- 
doing, but he felt less and less easy about his role in the universe. 
In 2010, Chi-X promoted him to a big new job. Global Head of 
Product; but before he took the job he came across an Internet 
post by Sal Arnuk and Joseph Saluzzi.* The post showed, in 
fine detail, how data about investors’ orders provided to high- 
frequency traders by two of the public exchanges, BATS and 
Nasdaq, helped HFT discern investors’ trading intentions. Most 
investors, Arnuk and Saluzzi wrote, “have no idea that the pri- 
vate trade information they are entrusting to the market centers 
is being made public by the exchanges. The exchanges are not 
making this clear to their clients, but instead are actively broad- 

* Arnuk and Saluzzi, the principals of Themis Trading, have done more than anyone to 
explain and publicize the predation in the new stock market. They deserve more lines 
in this book than they receive but have written their own book on the subject, Broken 



casting the information to the HFTs in order to court their 
order flow.” “It was the first credible evidence of Big Foot,” 
said Matt. He dug around on his own and saw that the glitches 
at BATS and Nasdaq that queered the market for the benefit 
of HFT weren’t flukes but symptoms of a systemic problem, 
and that “many other little market quirks were there that were 
potentially being exploited.” 

He was then in an awkward position: that of a public spokes- 
man for the new American-style stock market who doubted the 
integrity of that market. “I’m at the point where I no longer feel 
I can authentically defend high-frequency trading,” he said. “I 
look at us exporting our business model to all these different 
countries and I think. It’s like exporting a disease .” He was thirty- 
four years old, and married, with a one-year-old child. Chi-X 
was paying him more than $400,000 a year. And yet, with no 
idea what he was going to do to earn a living, he up and quit. 
“I don’t want to say I’m an idealist,” he said. “But you have a 
limited amount of time on this planet. I don’t want to be twenty 
years from now and thinking I hadn’t lived my life in a way I 
could be proud of.” He kicked around for the better part of a 
year before he thought to call Ronan, whom he’d met when 
Ronan came through to run cables for HFT inside his Canadian 
exchange. In October 2012 they met for coffee at the McDon- 
ald’s near Liberty Plaza, and Ronan explained he’d just left RBC 
to open a new stock exchange. “My first reaction was, I feel so 
bad for the guy,” said Matt. “He’s just destroyed his future. They’re just 
doomed. Then, afterwards, I asked myself, ‘What causes a bunch 
of people making a million a year to quit?’ ” He came back in 
November and asked Ronan some more questions about this 
new exchange. In December, Brad hired him. 

Standing in front of the whiteboard, Brad now reviewed the 



problem at hand: It was unusual for an investor to direct his bro- 
ker to send his order to one exchange, but that is what investors 
were preparing to do with IEX. But these investors had no way of 
determining if the Wall Street brokers followed their instructions 
and actually sent the orders to IEX. The report investors typi- 
cally received from their brokers — the Transaction Cost Analy- 
sis, or TCA — was useless, so sloppily and inconsistently compiled 
as to be beyond analysis. Some of it came time-stamped to the 
second; some, time-stamped in tenths of microseconds. None of 
it told you which exchange you traded on. As a result, there was 
no way to determine the context of any transaction, the event 
immediately before it and the one immediately after. If you didn’t 
even know the order of the trades in the stock market, you could 
hardly determine if you had traded at a fair price. “It’s a Pandora’s 
box of ridiculousness,” said Brad. “Just getting an answer to the 
question: ‘Where did I trade?’ It isn’t really possible.” 

“What if they [investors] send us their trade orders and we 
check them to see if they ever got here?” asked Rob Park sensibly. 

“We can’t,” said Don. “It violates our confidentiality agree- 
ment with brokers.” 

True. An investor might hand Bank of America an order and 
ask the Bank of America broker to route it to IEX. The inves- 
tor might also ask that IEX be permitted to inform him of the 
outcome. And yet Bank ol America might refuse, on principle, 
to allow IEX to inform the investor that they had followed his 
instructions — on the grounds that doing so would reveal Bank 
of America’s secrets! 

“Why can’t we just publish what happened?” asked Ronan. 

“It’s the banks’ information,” said Don. 

“We can't publish what happened to an investor’s trade because 
what happened to the investor is Goldman Sachs’s information?” 



Ronan was incredulous — but then he knew less about this than 
the others. 


“What can they do to us if we do it — shut us down?” 

“Probably just a slap on the wrist the first time,” said Don. 

Brad wondered aloud if it was possible to create a mechanism 
through which investors might be informed, in real time, where 
their brokers sent their stock market orders. “Like a security 
camera,” he said. “You don’t care if it’s even turned on. Just the 
fact that it’s there might alter behavior.” 

“It’s a finger in the eye of the brokerage community,” said 
Don. He wore a t-shirt that said I Love Aquatic Life, and tossed 
a rugby ball to himself, but he didn’t feel as comfortable as he 
wished to appear. All these other guys had worked at big Wall 
Street banks; none of them had ever had to deal with those 
banks as a customer. They didn’t know their market power. As 
Don later put it, “The brokers, if they all decide to hate us, we’re 
fucked. End of story.” He didn’t put it so bluntly to the others, 
maybe because he sensed that they all knew it. 

“It's like saying, ‘I think people are stealing in this office,’” 
said Brad, with growing enthusiasm. “I can run in and run out 
and run in and run out and keep checking and try to catch 
someone. Or I can install a camera. It may be plugged in — or 
not. But there’s still this camera. And whoever is fucking steal- 
ing my coffee pots won’t know if it’s on.” 

“We don’t really give a fuck if the investors use it,” added 
Ronan. “We just want the brokers scared they’ll check.” 

Somewhere in the big room a phone rang, and the sound was 
as jolting as a car honking in a small town in the middle of the 
night. The room was an open pit, with no barriers between 
the people in it, but the young men inside it behaved as if they 



worked with walls around them. They were, all but one, young 
men. The exception, Tara McKee, had been a research associate 
at RBC until Brad found her, in 2009, and asked her to be his 
personal assistant. (“The first time I met him, I said, ‘I don’t care 
what I do — I just want to work for him.’ ”) She’d followed him 
out when he left the bank, even after he tried to talk her out 
of it, as he couldn’t pay her properly and didn’t think she could 
tolerate the risk. The cast of technologists Brad had assembled at 
this new place Tara found even more peculiar than the one he’d 
put together at RBC. “For geniuses, they are really dumb,” she 
said. “Some of them are really pampered: They can’t even put 
together a cardboard box. They don’t think you do something. 
They think you call somebody.” 

They were also amazingly self-contained. This meeting con- 
cerned them all— compelling the big Wall Street banks’ coopera- 
tion might mean the difference between success and failure — but 
they all at least feigned indifference. The etiquette here was a kind 
of willed incuriosity — even about each other. “Communication 
with a lot of the guys is not that great,” said Brad. “It’s something 
we need to work on.” It was funny. To a man, they were puzzle 
solvers, and yet, to each other, they remained unsolved puzzles. 

Schwab looked over the desks and shouted, “Whose phone is 

“Sorry,” someone said, and the ringing stopped. 

“It’s a nanny,” said Don, of Brad’s security camera idea. “It’s 
demeaning. It could be a strain on the relationship.” 

“When you get patted down in the airport, do you hate the 
people who pat you down?” asked Brad. 

“I fuckin’ hate them,” said Don. 

“I say, ‘I’m glad you’re checking my bags, because that means 
you’re checking other people’s,’ ” said Brad. 



“The problem is that everyone is carrying marijuana through 
the checkpoint,” said Schwab. 

“If anyone gets fucking angry it’s because they’re guilty,” said 
Brad hotly. 

“I’m sorry,” said Don. “I’m fat and white and I’m not gonna 
bomb this airplane. I shouldn’t get extra swabbing.” He’d stopped 
tossing the rugby ball. 

“Is there some use for this other than policing brokers?” asked 
Schwab. He was asking, “Can we police them without their 
realizing it?” The person among them most adept at uncovering 
the secrets of others believed it was possible for IEX to keep its 
own affairs secret. 

“No,” said Brad. 

“So it’s a nanny,” said Schwab with a sigh. 

“Broker Nanny,’ 1 said Don. “It’s a great name. Shame we can’t 
patent it.” 

The meeting went quiet. This was just one of a thousand 
arguments they’d had in designing the exchange. The group was 
roughly split — between people (Ronan and, to a lesser extent, 
Brad) who wanted to pick a fight with the biggest Wall Street 
banks, and people who thought it was insane to pick that fight 
(Don and, to a lesser extent, Schwab). Rob and Matt hadn’t yet 
come clean, but for different reasons. After his initial suggestion 
had been swatted away, Rob had gone silent. “Rob is farthest 
from the chaos,” said Brad. “He doesn’t meet with brokers. The 
solutions to the problems they [the Wall Street brokers] create 
are illogical because they solve a problem that is illogical.” 

Matt Trudeau, also quiet, often tended to step back and 
observe. “I’ve always felt a little outside the groups of people 
I hung around with,” he said. He was a natural conciliator as 
web. He may have quit his job on principle, but he didn’t enjoy 



conflict, even the internal kind. “I might not be jaded enough,” 
Matt now said carefully. “But let’s say we launch and we’re 
wildly successful and we never have to roll this out.” 

That thought was dead on arrival: No one believed they 
would be wildly successful the moment they launched— least 
of all Matt. He knew firsthand what happened when a new 
exchange opened: nothing. Chi-X Canada was now a huge 
success — 20 percent of the Canadian market — but in its first 
month it had traded 700 shares total. Entire days passed with- 
out a single trade on that exchange; and the next few months 
weren’t much better. And that was what success looked like. 
IEX didn’t have the luxury of going months without activity. 
Their new stock exchange didn’t need to be an instant sensa- 
tion, but it had to host enough trading to illustrate the positive 
effects of honesty. They needed to be able to prove to inves- 
tors that an explicitly fair exchange yielded better outcomes for 
investors than all the other exchanges. To prove the case, they 
needed data; to generate that data, they needed trades. If the 
big Wall Street banks colluded to keep trades off IEX, the new 
exchange would be stillborn. And they all knew it. 

“They’re gonna be pissed,” said Schwab finally. 

“We’re in a fight,” said Brad. “If every client felt like their 
instructions were being followed, we wouldn’t be having this 
discussion. It’s not about IEX wanting to go punch some bro- 
ker in the face for no reason. It’s not about saying, Who is our 
enemy?’ It’s about saying who we are aligned with. We’re aligned 
with the investor.” 

“They’re still gonna be pissed,” said Schwab. 

“Are we really in the police business?” asked Don. 

“Maybe we don’t have to have it at all,” added Schwab. 
“Maybe we just have to create the illusion we have it. We talk to 



the buy side about having it, and they whisper to their brokers — 
that might be enough.” 

“But they’ll all know,” said Don. “They know we have to 
keep the brokers’ junk private. And the broker has to keep the 
clients’ junk private. And the client can’t opt out.” 

Brad offered one last idea: a chat room in which investors 
could converse with their brokers as the trade was happening. 
“Or they can always get their broker on the phone and say, ‘Tell 
me what the fuck is going on,’ ” he said. “It’s always been a 

“They’ve never done it,” said Ronan. 

“They’ve never been motivated to do it,” said Matt. True: 
Investors had never been given a compelling reason to favor one 
stock exchange over another. 

“You get Danny Moses in a chat room with Goldman,” said 
Brad, referring to the head trader at Seawolf. “He’ll ask them.” 

“But Danny’s a bit argy-bargy,” said Ronan. 

“ Argy-bargy , I like that,” said Don. 

Ronan had been teaching Don Irish epithets, one at a time. 
“You got wanker. Tosser. Now you got argy-bargy,” said Ronan. 

“You do nothing, and everyone does what they want,” said 
Brad. “You do something and you can influence behavior. But, 
by creating the tool, do we incentivize behavior we want to 
eliminate? By shining the light, do we create a gray zone, just 
outside the light? Is it like Reg NMS, where you create the very 
thing you’re trying to get rid of?” 

“Shining a light creates shadows,” said Don. “If you try to 
create this bright line, you are going to create gray zones on 
either side.” 

“If we sincerely believe it creates too many blind spots, we 
might not want to do it,” said Brad. 



“If we bill it as a nanny and she’s drunk on the couch, are we 
gonna look like assholes?” added Don. “Better not to have a 
nanny at all. Just leave the kids home alone.” 

“If you can think of any other possible use for this fucker, 
that would help,” said Schwall, who clung to his hope that they 
might disguise their actions. That they might be secret cops. 

“I’m less bullish on this than I was before,” said Brad. “I’ll 
be honest. Because a drunk nanny might not be better than no 
nanny at all.” 

“How drunk can a nanny get?” asked Ronan idly. 

Brad tossed the marker back into the whiteboard bin. “You 
can see why the client has been left in the dust,” he said. “The 
system is designed to leave the client in the dust.” Then he 
turned to Don. “At Nasdaq did they talk about this?” 

“No,” said Don, leaning back against the window. 

For a moment, Brad looked at Don, and at the view that he 
only partly concealed. In that moment, he might as well have 
been, not on the inside of his new exchange looking out, but 
on the outside looking in. How did they seem to others? To the 
people out there ? Out there, where the twin symbols of American 
capitalism once loomed, reduced in a few hours to a blizzard of 
office memos and a ruin. Out there, where idealism was either 
a ruse or a species of stupidity, and where the people who badly 
needed them to succeed hadn’t the faintest idea of their exis- 
tence. But out there a lot of things happened. People built new 
towers to replace the old ones. People found strength they didn’t 
know they had. And people were already coming to their aid, 
and bracing for the war. Out there, anything was possible. 



O n the morning of September 11, 2001, Zoran Perkov 
took the subway from his home in Queens to Wall Street, 
as he did every day. As usual, he wore headphones and 
listened to music, and pretended that the other people on the 
train didn’t exist. The difference between that morning and all 
the others was that he was running late, and the people on the 
train were harder than usual to ignore. They were talking to each 
other. “Nobody talks to each other,” said Zoran. “It was a weird 
feeling, when you feel something is off.” He was twenty-six 
years old, tall and broad, with hooded eyes that saw everything 
in one shade of gray or another. Born in Croatia, into long lines 
of fishermen and stonemasons, he’d moved with his parents to 
the United States when he was a small child. He’d grown up 
in Queens, and he worked on a tech help desk for the crypti- 
cally named Wall Street Systems, at 30 Broad Street, immedi- 
ately next door to the New York Stock Exchange. His job bored 
him. What precisely he did on Wall Street Systems’ tech help 



desk didn’t matter. He wouldn’t be doing it much longer. In 
the next few hours, he’d discover a reason for doing something 
else. This discovery — and the clear sense of purpose that came 
with it would put him on a course to be of serious use to Brad 

The subway car was a silent movie. Zoran watched the people 
in it talking to each other all the way to Wall Street. Ascending 
from the hole in the ground in front of Trinity Church and into 
the morning light, he noticed the necks tilted back and the eyes 
gazing upward. He, too, looked up, just as the second plane hit 
the South Tower. “You couldn’t see the plane,” he said. “You 
just saw this explosion.” 

He took off his headphones and heard the sounds. “All around 
people crying, people screaming, people puking.” He saw peo- 
ple running up Broadway. He crossed the street and went to 
work. Work isn t work for me,” he said. “I got friends there. I 
went to find out what is going on.” Outside the front door, he 
spotted the same pretty woman with a cigarette he always saw 
on his way in. (“You know, the one hot chick in the building.”) 
She was smoking but also crying. He went upstairs, checked 
in with his friends, and called some guys he’d grown up with 
who worked on or around Wall Street. One of them worked in 
the Twin Towers — which tower Zoran couldn’t recall. A couple 
more worked in the buildings around the towers. He reached 
them and they agreed to use his office as their meeting point. 
When his friend from the Twin Tower arrived, he said that on 
his way out he’d heard the bodies hitting the ground. 

The small group of five friends set out to escape. They dis- 
cussed strategy. Zoran argued for walking out, up Broadway; 
the others voted to leave on the subway. “Democracy won,” said 
Zoran, and back down into the Wall Street station they went. It 



turned out that this was not an original idea. The crowds forced 
them apart; three of them squeezed into one car, while Zoran 
and another pushed into the next car. “It was such a mixed 
crowd,” said Zoran, “not your usual subway crowd.” There 
were all these Wall Street people; guys from the stock exchange 
in their colored jackets; people you just never saw there. The car 
lurched out of the station and into the dark tunnel, then stopped. 
“That’s when my ears popped,” said Zoran. “Like when you go 
swimming under water.” 

The tunnel tilled with smoke. Zoran had no idea what had 
happened — why his ears had popped, why the tunnel was full 
of smoke — but he noticed a guy trying to open a window, and 
he hollered at him to stop. Who gave you the authority? the guy 
screamed back at Zoran. “It’s smoke'' Zoran shouted. “Breathe 
it. Die. It’s that fucking simple.” The window stayed shut, but 
the car remained fractious and unsettled. The car holding his 
other friends was tranquil. People bent over, praying. 

The conductor came on and announced that the train needed 
to return to the Wall Street station. To general concern, the guy 
who drove the tram walked from the front car to the back car, 
did whatever needed to be done to allow the train to go the 
wrong way inside a tunnel, and jolted it back Irom whence it 
had come. But not completely: Only the front two cars gained 
access to the platform. The people in what was now the rear of 
the train needed to file out through the cars to reach the exit. 

That’s when Zoran noticed the old man — his neighbor, in a 
crowd trying to form a line to exit the train. “He’s got a cane,” 
said Zoran. “He’s in an old suit — he’s gotten thinner and smaller, 
so it doesn’t fit him very well. I remember thinking: I should 
probably make sure this guy doesn’t get crushed. So I just kind of kept 
him in front of me. I felt responsible for him.” Half-guiding the 



old man, he nudged his way back up the steps of the subway sta- 
tion and onto Wall Street. Then everything went totally black. 
“We get to street level, and I had to realize it was street level,” 
said Zoran. And I lost the old guy. From that moment I was just 
paying attention to everything around me.” 

He now couldn’t see, but he could hear people shouting. 
“Over here! Over here!” he heard someone scream. He and 
the friend who’d been in the subway car with him followed 
the sound of the voices, walking into what turned out to be 
the American Express building — though Zoran didn’t realize it 
until they’d been inside for a minute. What he noticed was the 
pregnant woman, sitting on the floor with her back against a 
wall. He went to her, made sure she wasn’t about to give birth, 
then gave her his phone, which still worked. The black air out- 
side began to acquire a color. “For some reason everything had 
this beige-like tone, ’ he recalled. He could now see more or less 
where they were, and which direction was which. A cop inside 
the building said, You need to stay in here.” Zoran grabbed his 
triend and left. They walked east and north until they arrived at 
some faceless apartment buildings on the Lower East Side. “It’s 
the projects, said Zoran, “and people are coming out with cups 
of water and all of their cordless phones. To help. That’s when I 
started to cry.” 

Eventually they reached the FDR Drive and continued due 
north. That might have been the oddest feeling of the entire 
morning, that walk along a stretch of the FDR. They were 
alone. It was quiet. For an amazingly long time, the only human 
being they encountered was a half-dressed cop who roared past 
them on a motorbike toward the catastrophe. Then the papers 
began to flutter down from above. On them Zoran could read 
the address of the World Trade Center. 



To say that Zoran found the whole experience exhilarating — 
well, that wouldn’t be quite right, though, as he told his story, 
he said that “somehow I feel guilty about telling it.” It was more 
that there hadn’t been even a moment when he had felt he didn’t 
know what he should do next. He’d been jarred into a new kind 
of awareness, and interest in the people around him, and he liked 
the feeling. His reactions had surprised him into an observation 
about himself. “I was impressed that I did not fall apart,” he said. 
“I didn’t use it as an excuse for anything. What it tells me is that 
I wasn’t afraid of those situations. I like being front and center. I 
like being in a drama.” He could even pinpoint the moment he 
realized he was better suited to a crisis than he expected himself 
to be. “It was when I realized I’ve started to give a shit about 
other people,” he said. 

Two days later he returned to work, but he’d been biffed from 
an ill-defined career path onto another, clearer one. He wanted 
to be in a job that required him to perform in a crisis. If you 
worked on the technology end of Wall Street and were looking 
for pressure, you ran an electronic stock market. By early 2006, 
that’s what Zoran was doing — at Nasdaq. “They just sat me in 
front of four machines with buttons that could, like, destroy 
everything,” he said. “It was the best thing in the world. Every 
day was the Super Bowl. The value of what you were doing felt 
so high.” The feeling of the job was hard to get across to anyone 
who wasn’t a technologist, but there was definitely a feeling to 
it. “Put it this way,” said Zoran. “If I fuck up, I’m going to be in 
the news. I’m the only one who can break it, and if it breaks I’m 
the only one who can fix it.” 

He’d learned this the hard way, of course. Not long after he 
started at Nasdaq, he’d broken one of the markets. (Nasdaq has 
owned several markets — Nasdaq OMX, Nasdaq BX, INET, 



PSX.) It happened when he was making changes to the system 
during trading hours. He entered a command, then heard the 
people around him panicking; but he failed to immediately con- 
nect one event to the other. A former Nasdaq colleague recalled 
the ensuing bedlam. I remember seeing people running around 
and screaming while it was happening,” he said. Zoran looked up 
at the stock market on his computer screen: It was frozen. It took 
him a few seconds to realize that, even though the thing he’d 
been working on should have had no connection to the market 
in real time, he had somehow shut his entire market down. It 
took him another few seconds to see exactly how he had done 
it. Then he fixed it, and the market resumed trading. From start 
to finish the crisis had lasted twenty-two seconds. Twenty-two 
seconds, during which all trading had simply ceased. “I remem- 
ber sitting there and thinking: I’m done,” said Zoran. “The CTO 
[chief technology officer] saved me. He said, ‘How can you get 
rid of a guy who makes a mistake, stops it, and fixes it?’ ” 

Still, the event shaped him. “I said, ‘How do I never do that 
again? said Zoran. “I started really jumping into how to control 
large-scale complex systems. I became a student of complexity — 
defined as something you cannot predict. How do you have 
stability in a system that is by its nature unpredictable?” He read 
everything he could find on the subject. One of his favorite 
books was actually called Complexity, by M. Mitchell Waldrop. 
His favorite paper to pass out was “How Complex Systems Fail,” 
an eighteen-bullet-point summary by Richard I. Cook, now a 
professor of health care systems safety in Sweden. (Bullet Point 
#6: Catastrophe is always just around the corner.) “People think that 
complex is an advanced state of complicated,” said Zoran. “It’s 
not. A car key is simple. A car is complicated. A car in traffic is 



A stock market was a complex system. One definition of a 
complex system was a place where, as Zoran put it, “Shit will 
break and there is nothing you can do about it.” The person 
whose job it was to make sure shit didn’t break ran two kinds 
of career risks: the risk of shit breaking that was within his con- 
trol, and the risk of shit breaking over which he had no control. 
Zoran continued to run one of the Nasdaq markets. Eventually, 
the company handed him bigger markets to run; and the risk 
of running them grew. By the end of 2011, he was overseeing 
all of Nasdaq’s market running. (Head of Global Operations, 
he was called.) He had spent the better part of six years add- 
ing complexity to those markets, for reasons he did not always 
understand. The business people would just decide to make 
some change, which it was his job to implement. “The Post- 
Only order type was the first thing that got me,” said Zoran, 
of the order designed to be executed only if the trader received 
a kickback from the exchange. “What the fuck is the point of 
a Post-Only order?” He was somehow expected to cope with 
the demands made on Nasdaq’s markets by Nasdaq’s biggest 
customers (high-frequency traders) and, at the same time, keep 
those markets safe and stable. It was as if a pit crew had been 
asked to strip down the race car, rip out the seat harnesses, and 
do whatever else they might to make the car go faster than it 
ever had before — and at the same time reduce the likelihood 
that the driver would die. Only in this case, if the driver was 
killed, blame for his death would be assigned, arbitrarily, to one 
member of the pit crew. Him. 

This state of affairs led to a certain skittishness in the pit crew. 
It wasn’t just that the high-frequency traders were demanding 
changes to the market that would benefit only them: The mere 
act of changing the system increased the risks to everyone who 



depended on it. Adding code and features to a trading system 
was like adding traffic to a highway: You couldn’t predict the 
consequences of what you had done; all you knew was that you 
had made the situation more difficult to understand. “No one is 
trying to control what they don’t know,” said Zoran. “And what 
they don’t know is growing.” He thought of himself as good in 
a crisis, but he didn’t see the point of manufacturing crises so 
that he might demonstrate his virtuosity. He was also far less 
suited to managing a bunch of market runners than he was to 
running a market himself. He had no gift for corporate politics. 
Every day, he liked his job less and less — until, in March 2012, he 
was fired, whereupon he got a phone call from Don Bohemian. 
Don wanted Zoran to run the market for IEX. “I’m not going 
to pitch you just now, mainly because we have no money and we 
don’t even know what we’re going to do,” said Don. “But I may 
pitch you later. ’ Don knew that Zoran had been a casualty of an 
office political battle, and, more to the point, that he was maybe 
the best exchange runner he’d ever seen. “He has all the quali- 
ties,” said Don. “Poise under pressure. The ability to understand 
a complex and vast system. And be able to think into it — imagine 
into it — accurately. To diagnose and foresee problems.” 

It was a little unsettling that the geeks who now ran the 
financial markets were also expected to have the nerves of a test 
pilot. But by the time Don approached Zoran, it had grown 
clear that the investing public had lost faith in the U.S. stock 
market. Since the flash crash back in May 2010, the S&P index 
had risen by 65 percent, and yet trading volume was down 50 
percent: For the first time in history, investors’ desire to trade 
had not risen with market prices. Before the flash crash, 67 
percent of U.S. households owned stocks; by the end of 2013, 
only 52 percent did: The fantastic post-crisis bull market was 



noteworthy for how many Americans elected not to participate 
in it. It wasn’t hard to see why their confidence in financial 
markets had collapsed. As the U.S. stock market had grown less 
comprehensible, it had also become more sensationally erratic. 
It wasn’t just market prices that were unpredictable but the mar- 
ket itself — and the uncertainty it created was bound to extend, 
sooner or later, to the many foreign stock markets, bond mar- 
kets, options markets, and currency markets that had aped the 
U.S stock market’s structure. 

In March 2012 the BATS exchange had to pull its own initial 
public offering because of “technical errors.” The next month, 
the New York Stock Exchange canceled a bunch of trades by 
mistake because of a “technical glitch.” In May, Nasdaq bungled 
the initial public offering of shares in Facebook Inc. because, in 
essence, some investors who submitted orders to buy those shares 
changed their minds before the price was agreed upon — and 
certain Nasdaq computers couldn’t deal with the faster speeds at 
which other Nasdaq computers allowed the investors to change 
their minds. In August 2012, the computers of the big HFT firm 
Knight Capital went berserk and made stock market trades that 
cost Knight $440 million and triggered the company’s fire sale. 
In November, the NYSE suffered what was termed a “match- 
ing engine outage” and was forced to halt trading in 216 stocks. 
Three weeks later, a Nasdaq employee clicked the wrong icon 
on his computer screen and stopped the public offering of shares 
in a company called WhiteFlorse Finance. In early January 2013, 
BATS announced that, because of some unspecified computer 
error, it had, since 2008, inadvertently allowed trades to occur, 
illegally, at prices worse (for the investor) than the National Best 
Bid and Offer. 

That was just a sampling from a single year of what were usu- 



ally described as “technical glitches” in the new, automated U.S. 
stock markets: Collectively, they had experienced twice as many 
outages in the two years after the flash crash as in the previous 
ten. The technical glitches were accompanied by equally bewil- 
dering irregularities in stock prices. In April 2013, the price of 
Google’s shares fell from $796 to $775 in three-quarters of a 
second, for instance, and then rebounded to $793 in the next 
second. In May the U.S. utilities sector experienced a mini-flash 
crash, with stocks falling by 50 percent or more for a few seconds 
before bouncing back to their previous prices. These mini-flash 
crashes in individual stocks that now occurred routinely went 
largely unnoticed and unremarked upon.* 

Zoran liked to argue that there were actually fewer, not more, 
“technical glitches” in 2012 than there had been in 2006 — it 
was only the financial consequences of system breakdowns that 
had grown. He also took issue with the word “glitch.” (“It’s the 
worst word in the world.”) When some machine malfunctioned 
and a stock market came under scrutiny, the head of that mar- 
ket usually had no clue either what had happened or how to 
fix it: He was at the mercy of his technologists. But he had to 
say something, and so he said that there had been a “technical 
glitch.” It was as if there was no way to explain how the financial 
market actually worked — or didn’t — without resorting to fuzzy 

* Eric Hunsader, the founder of Nanex, a stock market data company, is a fantastic 
exception to the general silence on this subject. After the flash crash, it occurred to 
him to use his data to investigate what had gone wrong, and the search never really 
ended. “Almost every rock t overturn, something nefarious crawls out from under it,” 
he said. Hunsader has brilliantly and relentlessly described market dysfunction and 
pointed out many strange micro-movements in stock prices. When the last history of 
high-frequency trading is written, Hunsader, like Joe Saluzzi and Sal Arnuk of The- 
mis Trading, deserves a prominent place in it. 



metaphors and meaningless words * If stock market computer- 
related problems were to be reduced to a single phrase, Zoran 
preferred it to be “normal accidents.”' 1 " 

When Bollerman called him again, late in the summer of 
2012, IEX had an idea, and the first glimmer of hope that they 
would find money. That the idea was also idealistic made Zoran 
skeptical; he wasn’t sure it was possible ever to make a financial 
market fair. But he absolutely loved the idea of running a mar- 
ket he helped to design — to limit the number of things in it he 
could not control. He came in to IEX to meet Brad and Rob 
and John Schwall and Ronan. Brad and Schwab and Rob liked 
him, Ronan not so much. “What put me off is that he wouldn’t 
shut the fuck up,” said Ronan. 

His first few months on the job, Zoran drove everyone nuts. 
Lacking a market crisis, he proceeded to create a social one. 
They’d tell him about some new feature they had thought to 
introduce into the system and ask, “Will this make the system 
harder to manage?” To which Zoran would reply, “It depends 
on your definition of ‘harder.’ ” Or they would ask him if some 
small change in the system would cause the system to become 
less stable — to which Zoran would reply, “It depends on your 
definition of ‘stable.’ ” Every question he answered with an 
uneasy chuckle, followed by some other question. A rare excep- 
tion came when he was asked, “Why do you always answer a 
question with another question?” “Clarity,” he said. 

Zoran also seemed to assume that his new colleagues would 

* “Glitch” belongs in the same category as “liquidity” or, for that matter, “high- 
frequency trading.” All terms used to obscure rather than to clarify, and to put minds 
to early rest. 

f From a book of that name by Charles Perrow. 



fail to understand the difference between what he could control 
and what he couldn’t. In one thirty-day span after he joined IEX, 
he shot out fifteen emails on this one subject — to hammer home 
the mystery inherent in any stock market technological failure. 
He even invited a speaker to come in to reinforce the point. 
“It was one the few times that the people in the room wound 
up at each other’s throats,” said Brad. “The tech people were 
all agreeing with him, and the business people were saying, ‘If 
something melts down, how could it not be someone’s fault?’ ” 
Brad’s breaking point came after the guest speaker had left and 
Zoran circulated a blog post called “A Short Story on Human 
Error.” The gist of it was that when complex systems broke, it 
was never the fault of any one person. The post described some 
computer catastrophe and then concluded, . . you’ll notice 
that it wasn’t just one little thing that caused it. It wasn’t the 
developer who just so happened to delete the wrong table. It was 
a number of causes that came together to strike hard, all of them 
very likely to be bigger issues inside the organization rather than 
a problem with the individual.” At which point Brad finally 
walked the ten yards from his desk to Zoran’s desk and shouted, 
“Stop sending these fucking emails!” 

And he did, finally. “I know what to do when things are 
exploding around me,” he later said. “But when nothing is 
exploding, the overthinking comes into play.” 

Initially Brad was mystified: How could a guy who thrived 
under pressure also have such a fear of being blamed if things 
went wrong? “He’s so good in a crisis,” said Brad later. “In 
game-time situations. Under pressure. I’ve seen it. But it’s like 
a quarterback who is great in the game, then spends the other 
six days explaining how it isn’t his fault if he throws an inter- 
ception. ‘Dude, your passer rating is 110. Stop it .” ’ Brad realized 



something: “It comes from a sense of insecurity that comes from 
the fact that he will be more recognized when things go wrong 
than when things go right.” Brad further realized that the prob- 
lem was not peculiar to Zoran but general to Wall Street tech- 
nologists. The markets were now run by technology, but the 
technologists were still treated like tools. Nobody bothered to 
explain the business to them, but they were forced to adapt to its 
demands and exposed to its failures — which was, perhaps, why 
there had been so many more conspicuous failures. (The excep- 
tion was the high-frequency trading firms, where the technolo- 
gists were kings. But then, the HFT firms didn’t have clients.) 
Nasdaq’s famously talented engineers were an extreme Wall 
Street case. The constant pressure on Nasdaq’s tech guys to adapt 
the stock markets’ code to the needs of high-frequency trad- 
ers had created a miserable, politicized workplace. The Nasdaq 
business guys foisted all these unreasonable demands on the tech 
guys and then, when the demands busted the system, blamed 
the tech guys for the failure. The tech guys all wound up with 
this abused animal quality to them. “You just have to unabuse 
them,” Brad explained, “and let them know they aren’t going to 
be blamed just because something goes wrong.” We all know that 
things will go wrong and it isn’t necessarily anyone’s fault. 

Rob and John Schwab seemed to agree that this was the 
correct approach to take with the people they hired from Nas- 
daq: to tell them over and over that they weren’t to blame for 
whatever had just happened, to include them in every business 
discussion so that they could see why they could be a part of 
it, and so on. Ronan had no patience for any of it. “C’mon, 
they came from a corporate American job,” he said. “They 
didn’t come from Auschwitz.” On the other hand, in time, 
even Ronan saw that Zoran possessed useful qualities he hadn’t 



at first perceived. “Someone who will be good at running the 
market — you need to be the most paranoid fuck in the world,” 
said Ronan. “And he’s the most paranoid fuck in the world. 
He thinks ten steps down the road of what could go wrong — 
because he’s thinking of what could happen to him if it goes 
wrong. He’s really good at it.” 

On the morning of October 25, 2013, Zoran Perkov took the 
subway from his home to Wall Street, as he always did. As usual, 
he read some book or white paper, and tried to pretend that the 
people around him didn’t exist. The difference between that 
morning and the others was that he was running early and had 
a stock market to open — and it was unlike any market he’d ever 
run. Spare, clean, single-minded, and built from the ground up 
by people he not only admired but now trusted. “Every single 
morning, the system is stateless,” he said, of exchange matching 
engines generally. “It doesn’t know what it’s supposed to do. 
Ninety-nine percent of the time, it’s the same thing it did the 
day before.” On this day, that could not possibly have been true, 
as the IEX matching engine had never actually done anything. 
Zoran sat down at his desk in IEX’s office and punched a few 
buttons and watched code scroll down his screen. He pulled out 
an old, battered computer mouse — then noticed it was dead. He 
frowned. “It’s my war mouse,” he said. “Every single market I 
have opened in the past ten years has been with this mouse.” He 
knocked it against the desk, realized that its battery had probably 
died, and wondered, briefly, how to replace it. “My wife mocks 
me because I can’t work the microwave oven but I can run a 
market,” he said. He switched out his war mouse for another, 
and checked his computer screens. The seconds ticked down; 
it was approaching nine thirty in the morning, when the U.S. 
stock market would open and, with it, this new market inside of 



it that aimed to transform it. He waited and watched for some- 
thing to go wrong. It didn’t. 

A minute before nine thirty, Brad walked over to Zoran’s 
desk: By popular agreement, Brad was to open the market that 
first day. He looked down at the keyboard, perplexed. 

“What do I do?” he asked. 

“Just hit Enter,” said Zoran. 

The entire room counted down the final seconds before the 

“Five . . . four . . . three . . . two . . . one.” 

Six and a half hours later, the market closed. Zoran had no 
idea whether the market as a whole had finished up or down for 
the day. Ten minutes after that he could be found, alone, pacing 
outside the 9/11 memorial, smoking a cigarette. “This is like the 
first day of the battle against complacency,” he said. 

TWO AND A half months later, sixteen people — the chief execu- 
tives or the head traders of some of the world’s biggest stock 
market money managers— gathered in a conference room on 
top of a Manhattan skyscraper. They’d flown in from around the 
country to hear Brad describe what he’d learned about the U.S. 
stock market since IEX had opened for trading. From that trad- 
ing, he’d gotten new information. To afford people interested in 
the truth even a glimpse of it was now considered faintly sedi- 
tious.* “This is the perfect seat to figure all this out,” said Brad. 

* In March 2013, the Commodity Futures Trading Commission, a derivatives regulator, 
ended its nascent program to give outside researchers access to market data after one of 
those researchers, Adam Clark-Joseph, of Harvard University, used the data to study the 
tactics of high-frequency traders. The commission shut down the research after lawyers 
for the Chicago Mercantile Exchange wrote the regulators a letter arguing that the data 



“It’s not like you can stand outside and watch. We had to be in 
the game to see it.” 

The sixteen investors controlled roughly $2.6 trillion in stock 
market investments among them, or roughly 20 percent of the 
entire U.S. market. Collectively, they paid to the big Wall Street 
banks roughly $2.2 billion of the $11 billion a year the Street 
earned from stock market commissions.* They weren’t exactly 
of one mind or spirit. A few of them were also investors in 
IEX, but most were not. A couple held the knowing, seemingly 
grown-up view that it was naive to think that idealism could 
have any effect on Wall Street. A few thought it was important 
to remember that technology had lowered their trading costs 
from what they had been decades earlier — and half-turned a 
half-blind eye to the stunts Wall Street intermediaries had pulled 
to prevent technology from lowering those costs even further. 
But whatever their predispositions, they were all at least a little 
bit angry, because they all had spent the past few years listening 
to Brad’s descriptions of the inner workings of the U.S. stock 
market. They now thought of him less as a guy trying to sell 
them something than as a partner, in a possibly quixotic attempt 
to fix a financial system that had become deeply screwed up. 
“You kind of know what’s going on, but you don’t have a good 
explanation for it,” said one. “He gave us the explanation.” A 
second said, “This isn’t about execution. It’s about a movement. 

Clark-Joseph had collected belonged to the high-frequency traders, and that sharing it 
was illegal. Before he was booted out of the place, Clark-Joseph showed how HFT firms 
were able to predict price moves by using small loss-making stock market orders to glean 
information from other investors. They then used that information to place much bigger 
orders, the gains from which more than compensated for the losses. 

* Estimates of commission paid to Wall Street banks for stock market trades in 2013 
range from $9.3 billion (Greenwich Associates) to $13 billion (the Tabb Group). 



I’m sick and tired of getting fucked. When I go into the market 
I want to know it’s clean.” A third added, “All of a sudden the 
market is all about algos and routers. It’s hard to figure this stuff 
out. There’s no book you can read. It’s just calling up people and 
talking to them. From the people at the banks you can’t get a 
straight answer to any question. You say, ‘The sky is blue.’ They 
say, ‘The sky is green.’ And you’re like, ‘What are you talk- 
ing about?’ And after half an hour it comes out that they have 
changed the definition of ‘sky.’ You know what you’re asking. 
They know what you’re asking. But they don’t want to answer 
it. The first time I talked to Brad and he was telling me how it 
all actually worked, my jaw must have hit the floor.” 

Another investor had a question about Brad. “Why does a 
person take the harder path? It’s a different situation from what 
you typically see. If it works, he will make money. But he’ll 
make less” than if he had stayed at RBC. 

The sixteen were all men. Most wore suits, with deep creases 
on the backs of their jackets that looked as if they’d been made 
with a bullwhip. They were different from the people who 
worked at the big Wall Street banks, and from the HFT guys. 
They were a lot less likely to bounce from firm to firm — a lot 
more likely to have a career in one place. They were more iso- 
lated, too: They didn’t know each other well and didn’t, until 
Brad suggested it, have any reason to organize themselves into 
any kind of fighting force. Many had just landed in New York 
City, and a few of them were obviously weary. Their tone was 
informal and familiar, with none of the usual jockeying for sta- 
tus. They might not all have been capable of outrage, but they 
were all still capable of curiosity. 

At some level, they all now realized that this thirty-five -year- 
old Canadian guy somehow had put himself in a position to 



understand the United States stock market in a way that the 
system, possibly, had never been understood. “The game is 
now clear to me,” Brad said. “There’s not a press release I don’t 
understand.” On August 22, Nasdaq had experienced a two- 
hour outage caused by what they said was a technical glitch 
in the SIP. Brad thought he understood why it had happened: 
Nasdaq threw vast resources into the cool new technology used 
by HFT to speed up its trading and little into the basic plumbing 
of the market used by the ordinary investor. “Nasdaq’s got this 
state-of-the-art facility for HFT,” he said. “Seventeen-kilowatt 
liquid-cooled cabinets and cross-connects everywhere and all 
this shit, and then they have this single choke point in the entire 
market — the SIP — and they don’t care about it. The B team is 
servicing it.” Four days later, two of the public exchanges, BATS 
and Direct Edge, revealed their intention to merge. In a normal 
industry, the point of a merger of two companies that performed 
identical functions would be to consolidate — to reduce costs. 
But, as a subsequent press release explained, both exchanges 
intended to remain open after the merger. To Brad the reason 
was obvious: The exchanges were both at least partially owned 
by high-frequency trading firms, and, from the HFT point of 
view, the more exchanges the better. 

A few weeks later, both Nasdaq and the New York Stock 
Exchange announced that they had widened the pipe that carried 
information between the HFT computers and each exchange’s 
matching engine. The price for the new pipe was $40,000 a 
month, up from the $25,000 a month the HFT firms had been 
paying for the old, smaller pipe. The increase in speed was two 
microseconds. Brad understood that the reason for this was not that 
the market was better off if HFT had information two microsec- 
onds faster than before, but that the high-frequency traders were 



all terrified of being slower than their peers, and the exchanges 
had figured out how to milk this anxiety. In a stock market now 
defined by its technology accidents, nothing actually happened 
by accident: There was a reason for even the oddest events. For 
instance, one day, investors woke up to discover that they’d 
bought shares in some company for $30.0001. Why? How was 
it possible to pay ten-thousandths of a penny for anything? Easy: 
High-frequency traders had asked for an order type that enabled 
them to tack digits on the right side of the decimal, so that they 
might jump the queue in front of people trying to pay $30.00. 
The reason for change was seldom explained; change just hap- 
pened. “The fact that it is such an opaque industry should be 
alarming,” Brad said. “The fact that the people who make the 
most money want the least clarity possible — that should be 
alarming, too.” 

Everything he had done with his new exchange was aimed 
at making it more transparent, and forcing Wall Street to fol- 
low. The sixteen investors understood IEX’s basic commercial 
strategy: to open as a private stock market and convert to a pub- 
lic exchange once their trading volume justified incurring the 
millions of dollars in regulatory fees they would have to pay. 
Although technically a dark pool, IEX had done something no 
Wall Street dark pool had ever done: It had published its rules. 
Investors could see, for the first time, what order types were 
allowed on the exchange, and if any traders had been given spe- 
cial access. IEX, as a dark pool, would thus try to set a new 
standard of transparency — and perhaps shame others into fol- 
lowing its example. Or perhaps not. “I would have thought one 
dark pool would have come forward after us and published their 
own rules,” Brad now told the investors. “ Someone must have 
nothing to hide. My prediction was six or seven out of the forty- 



four would have done it. None. Zero. There are now forty-five 
markets. On forty-four of them no one has any idea how they 
trade. Has it not dawned on anyone that it might actually be a 
good idea to tell people how the market works? People can look 
back on the financial crisis and say, ‘How can you give a mort- 
gage loan with no documentation? It’s preposterous.’ But banks 
did it. And now trillions of dollars of trades are being executed 
on markets where no one has any idea of how it works, because 
there is no documentation. Does that sound familiar?” 

Now he explained just how badly the market wanted to 
remain in the shadows — and just how badly the people at the 
heart of it wanted IEX to fail. Even before IEX opened, brokers 
from the big Wall Street banks went to work trying to under- 
mine them. One investor called to inform Brad that a repre- 
sentative of Bank of America had just told him that IEX was 
owned by high-frequency trading firms. On the morning IEX 
opened, a manager at an investment firm called ING sent out 
a mass email that looked as if it had been written on her behalf 
by someone inside one of the big Wall Street banks: “With the 
pending launch of IEX, we request that all ING Equity Trading 
executions be excluded from executing on the IEX venue. . . . 
I am still challenged by the conflict of interest inherent in their 
business model. As a result I request to opt out of trading with 
the IEX venue.” 

The employees of IEX had risked their careers to attack the 
conflicts of interest in the stock market. They had refused the 
easy capital from the big Wall Street banks — to avoid conflicts 
of interest. To avoid conflicts of interest, the investors who had 
backed IEX had structured their investments so that they them- 
selves did not personally profit from sending trades onto the 
exchange: Profits from their investment flowed through to the 



people whose money they managed. These investors had further 
insisted on having a stake of less than 5 percent in the exchange, 
to avoid having even the appearance of control over it. Before 
IEX launched, Brad had rebuffed an overture from Interconti- 
nentalExchange (known as ICE), the new owners of the New 
York Stock Exchange, to buy IEX for hundreds of millions of 
dollars — and walked away from the chance to get rich quick. 
To align their interests with the broader market’s, IEX planned 
to lower their fees as their volumes rose — for everyone who 
used the exchange. And on the day IEX opened for trading, this 
manager at ING — who had earlier refused to meet with them 
so that they might explain the exchange to her — was spreading 
a rumor that IEX had a conflict of interest.’ 

But then all sorts of bizarre behavior had attended IEX’s 
arrival in the U.S. stock market. Ronan had gone to a private 
trade conference — no media, lots of Wall Street big shots. It was 
the first time he had been invited to the exclusive event, and he 
intended to lie low. He was outside in the hallway on his way to 
the bathroom when someone said, “You know, they’re in there 
talking about IEX.” Ronan returned to the conference room and 
listened to the heads of several big public U.S. stock exchanges 
on a panel. All agreed that IEX would only contribute to the 
biggest problem in the U.S. stock market: its fragmentation. 
The market already had thirteen public exchanges and forty- 
four private ones: Who needed another? When it came time for 
audience participation, Ronan found a microphone. “Hi, I’m 

* ING, oddly enough, managed IEX’s then thirty-person 401(k) plan. Seeing this, John 
Schwall returned to his side career in private investigation. After some digging, he 
developed the opinion that any money manager who arbitrarily denied his clients access 
to markets might have violated his fiduciary responsibility. On those grounds, Schwall 
pulled the company’s 401(k) from ING. 



Ronan, and I think I went to go take a piss at the wrong time,” 
he said, and then gave a little speech. “Were not like you guys,” 
he concluded. “Or anyone else in the market. We’re an army 
of one.” He thought he was being calm and measured, but the 
crowd, by its standards, went wild — which is to say they actually 
clapped. “Jesus, I thought you were about to throw a punch,” 
some guy said afterward. 

The stock exchanges didn’t like IEX for obvious reasons, the 
big Wall Street banks for less obvious ones. But the more the 
big banks sensed that Brad was being regarded by big inves- 
tors as an arbiter of Wall Street behavior, the more carefully 
they confronted him. Instead of voicing their own objections 
to him directly, they would voice objections they claimed to 
have heard from other big banks. The guy from Deutsche Bank 
would say that the guy from Citigroup was upset that IEX was 
telling investors how to tell the banks to route to IEX — that sort 
of thing. “When I visited, they were all cordial,” said Brad. “It 
made me feel that the plan was to starve us out.” But without 
seeming to do so. The day before they’d opened for trading, a 
guy from Bank of America called Brad and said, Hey, buddy, 
what’s going on? I’d appreciate it if you’d say we’re being supportive. 
Bank of America had been the first to receive the documents 
they needed to connect to the exchange and, on opening day, 
were still dragging their feet in establishing a connection. Brad 
declined to help Bank of America out of its jam. “Shame is a 
huge tactic we have to deploy,” he said. 

Nine weeks after IEX launched, it was already pretty clear 
that the banks were not following their customers’ instructions 
to send their orders to the new exchange. A few of the investors 
in the room knew this; the rest now learned. “When we told 
them we wanted to route to IEX,” one said, “they said, Why 



would you want that? We can’t do that!’ The phrase ‘squealing 
pigs’ comes to mind.” After the first six weeks of IEX’s life, UBS, 
the big Swiss bank, inadvertently disclosed to one big investor 
that it hadn’t routed a single order onto IEX — despite explicit 
instructions from the investor to do so. Another big mutual fund 
manager estimated that, when he told the big banks to route to 
IEX, they had followed his instructions “at most ten percent of 
the time.” A fourth investor was told, by three different banks, 
that they didn’t want to connect to IEX because they didn’t 
want to pay the $300-a-month connection fee. 

Of all the banks that dragged their feet after their customers 
asked them to send their stock market orders to IEX, Goldman 
Sachs had offered the best excuse: They were afraid to tell their 
computer system to do anything it hadn’t done before. In August 
2013, the Goldman automated trading system generated a bunch 
of crazy and embarrassing trades that lost Goldman hundreds 
of millions of dollars (until the public exchanges agreed, amaz- 
ingly, to cancel them). Goldman wanted to avoid giving new 
instructions to its trading machines until it figured out why 
they had ceased to follow the old ones. There was something 
about the way Goldman had treated Brad when he visited their 
offices — listening to what he had to say, bouncing him up the 
chain of command rather than out the door — that led him to 
believe their excuse. He sensed that they were taking him seri- 
ously. After his first meeting with their stock market people, for 
instance, Goldman’s analysts had told the firm’s clients that they 
should be more wary of investing in Nasdaq Inc. 

The other banks — Morgan Stanley and J.P. Morgan were 
the exceptions — were mostly passive-aggressive, but there were 
occasions when they became simply aggressive. Employees of 
Credit Suisse spread rumors that IEX wasn’t actually mdepen- 



dent but owned by the Royal Bank of Canada — and so just a tool 
of a big bank. One night, in a Manhattan bar, an IEX employee 
bumped into a senior manager at Credit Suisse. “After you guys 
fail, come to me and I’ll give you a job,” he said. “Wait, no, 
everyone hates your fucking guts, so I won’t.” In the middle of 
their first day of trading, one of IEX’s employees got a call from 
a senior executive of Bank of America, who said that one of his 
colleagues had “ties to the Irish Mafia,” and “you don’t want to 
piss those guys off.” The IEX employee went to Brad, who just 
said, “Tie’s full of shit.” The IEX employee was less sure, and 
followed the call with a text. 

IEX employee: Should I be concerned? 

Bank of America employee: Yes. 

IEX employee: Are you serious? 

Bank of America employee: Jk [Just kidding]. 

IEX employee: Haven’t noticed any Irish guys following me. 

Bank of America employee: Be careful next time you get in 
your car. 

IEX employee: Good thing I don’t own a car. 

Bank of America employee: Well, maybe your gf’s car. 

Brad also heard what the big Wall Street banks were already 
saying to investors to dissuade them from sending orders to 
IEX: It’s too slow. For years, the banks had been selling the speed 
and aggression of their trading algos, along with the idea that, 
for an investor, slower always meant worse. They seemed to have 
persuaded themselves that the new speed of the markets actu- 
ally helped their clients. They’d even dreamed up a technical- 
sounding name for an absence of speed: “duration risk.” (“If you 
make it sound official, people will believe that it’s something you 



really need to care about,” Brad explained.) The 350-microsecond 
delay IEX had introduced to foil the stock market predator was 
roughly one-thousandth of the blink of an eye. But investors for 
years had been led to believe that one-thousandth of the blink of 
an eye might matter to them, and that it was extremely impor- 
tant for their orders to move as fast and aggressively as possible. 
Guerrilla! Raider! This emphasis on speed was absurd: No matter 
how fast the investor moved, he would never outrun the high- 
frequency traders. Speeding up his stock market order merely 
reduced the time it took for him to arrive in HFT’s various 
traps. “But how do you prove that a millisecond is irrelevant?” 
Brad asked. 

He threw the problem to the Puzzle Masters. The team had 
expanded to include Larry Yu, whom Brad thought of as the 
guy with the box of Rubik’s cubes under his desk. (The standard 
3x3-inch cube he could solve in under thirty seconds, and so he 
kept it oiled with WD-40 to make it spin faster. His cube box 
held more challenging ones: a 4x4-incher, a 5x5-incher, a giant 
irregularly shaped one, and so on.) Yu generated two charts, 
which Brad projected onto the screen for the investors. 

To see anything in the stock market, you have to stop try- 
ing to see it with your eyes and instead attempt to imagine it 
as it might appear to a computer, if a computer had eyes. The 
first chart showed the investors how trading on all public U.S. 
stock exchanges in the most actively traded stock of a single 
company (Bank of America Corp) appeared to the human eye 
over a period of ten minutes, in one-second increments. The 
activity appears constant, even frantic. In virtually every second, 
something occurs: a trade or, more commonly, a new buy or sell 
order. The second chart illustrated the same activity on all pub- 
lic U.S. stock exchanges as it appeared to a computer, over the 



course of a single second, in millisecond increments. All the mar- 
ket activity within a single second was so concentrated — within 
a mere 1.78 milliseconds — that on the graph it resembled an 
obelisk rising from a desert. In 98.22 percent of all milliseconds, 
nothing at all happened in the U.S. stock market. To a computer, 
the market in even the world’s most actively traded stock was an 
uneventful, almost sleepy place. “Yes, your eyeballs think the 
markets are going fast,” Brad said. “They aren’t really going that 
fast.” The likelihood an investor would miss out on something 
important in a third of a millisecond was close to zero, even in 
the world’s most actively traded stock. “I knew it was bullshit to 
worry about milliseconds,” said Brad, “because if milliseconds 
were relevant, every investor would be in New Jersey.” 

“What’s the spike represent?” asked one of the investors, 
pointing to the obelisk. 

“That’s one of your orders touching down,” said Brad. 

A few investors shifted in their seats. It was growing clear to 
them, if it wasn’t already so, that, if the stock market was the 
party, they were the punch bowl. They were unlikely to miss 
any action as the result of a delay of one-third of a millisecond. 
They were the reason for all the action! “Every time a trade 
happens at the exchange, it creates a signal,” said Brad. “In the 
fifty milliseconds running up to it — total silence. Then there is 
an event. Then there is this massive reaction. Then a reaction to 
that reaction. The HFT algos on the other side are predicting 
what you’ll do next based on what you just did.” The activity 
peaked roughly 350 microseconds after an investor’s order trig- 
gered the feeding frenzy, or the time it took for HFT to send 
its orders from the stock exchange on which the investor had 
touched down to all of the others. “Your eye will never pick up 
what is really happening,” said Brad. “You don’t see shit. Even 



if you’re a fucking cyborg you don’t see it. But if there was no 
value to reacting, why would anyone react at all?” The arrival of 
the prey awakened the predator, who deployed his strategies — 
rebate arbitrage, latency arbitrage, slow market arbitrage. Brad 
didn’t need to dwell on these; he’d already walked each of the 
investors through his earlier discoveries. It was his new findings 
that he wanted them to focus on.* 

On IEX’s opening day — when it had traded just half a million 
shares — the flow of orders through its computers had been too 
rapid for the human eye to make sense of it. Brad had spent the 
first week or so glued to his terminal, trying to see whatever he 
could see. Even that first week, he was trying to make sense of 
lines scrolling down his computer screen at a rate of fifty per sec- 
ond. It felt like speed-reading War and Peace in under a minute. 
All he could see was that a shocking number of the orders being 
sent by the Wall Street banks to IEX came in small 100-share 
lots. The HFT guys used 100-share lots as bait on the exchanges, 
to tease information out of the market while taking as little risk 
as possible. But these weren’t HFT orders; these were from the 
big banks. At the end of one day, he asked for a count of one 
bank’s orders: 87 percent of them were in these tiny 100-share 
lots. Why? 

The week after Brad had quit his job at the Royal Bank of 
Canada, his doctor noted that his blood pressure had collapsed 
to virtually normal levels, and he’d cut his medication in half. 
Now, in response to this new situation he couldn’t make sense 

* Sixty percent of the time that this feeding frenzy occurs on a public stock exchange, 
no trade is recorded. The frenzy comes in response to a trade that has occurred in some 
dark pool. The dark pools are not required to report their trades in real time; and so, on 
the official tape, the frenzy appears unprovoked. It isn’t. 



of, Brad had migraines, and his blood pressure was again spik- 
ing. “I’m straining to see patterns,” he said. “The patterns are 
being shown to me, but my eyes can’t pick them up.” 

One afternoon, an IEX employee named Josh Blackburn 
overheard Brad mention his problem. Josh was quiet — not just 
reserved, but intensely so — and didn’t say anything at first. But 
he thought he knew how to solve the problem. With pictures. 

Josh, like Zoran, traced his career back to September 11, 
2001. He’d just started college when a friend messaged him to 
turn on the TV, and he’d watched the Twin Towers collapse. 
“When that happened it was kind of a what can I do moment?” A 
couple of months later, he’d gone to the local air force recruit- 
ing center and attempted to enlist. They’d told him to wait 
until the end of his freshman year. At the end of the school year 
he’d returned. The air force sent him to Qatar, where a colonel 
figured out that he had a special talent for writing computer 
code; one thing led to another, and two years later he was in 
Baghdad. There he created a system for getting messages to 
all remote units, and another system for creating a Google- 
like map, before the existence of Google maps. From Baghdad 
he’d gone to Afghanistan, where he wound up being in charge 
of taking the data from all the branches of the U.S. military 
across all battlefields and turning it into a single picture the 
generals could use to make decisions. “It told them everything 
that was going on, real-time, on a twenty-foot wall map,” Josh 
said. “You could see trends. You could see origins of rocket 
attacks. You could see patterns in when they occurred — the 
attacks on [U.S. Army base] Camp Victory would come after 
afternoon prayer. You could see what the projections were [of 
where and when the attacks might occur] and how they com- 
pared to where attacks actually happened.” The trick was not 



simply to write the code that turned information into pictures 
but to find the best pictures to draw — shapes and colors that 
led the mind to meaning. “Once you got all that stuff together 
and showed it in the best way possible, you could find pat- 
terns,” Josh said. 

The job was hard to do, but, as it turned out, harder to stop 
doing. When his first tour of duty was up, Josh reenlisted, and 
when that tour ended, he re-upped again. When his third tour 
was over, he saw the war winding down and his usefulness 
diminish. “You find it very difficult to come home from,” said 
Josh. “Because you see the impact of your work. After that, 

I couldn’t find any passion in anything I did, any meaning.” 
Coming home, he looked for a place to deploy his skill — and 
a friend in finance told him about an opening in a new high- 
frequency trading firm. “In the war, you’re trying to use the 
picture you create to take advantage of the enemy,” said Josh. 
“In this case, you’re trying to take advantage of the market.” He 
worked for the HFT firm for six weeks before it failed, but he 
found the job unsatisfying. 

He’d come to IEX in the usual way: John Schwall had found 
him while trolling on Linkedln and asked him to come for an 
interview. At that point, Josh was being inundated with offers 
from other high-frequency trading firms. “There was a lot of 
‘we are elite,’ ” he said. “They kept hitting the elite thing.” He 
didn’t care all that much about being elite; he just wanted his 
work to mean something. “I came in for an interview on Fri- 
day. Saturday they made me an offer. Brad said, we’re going to 
change the way things work. But I didn’t really know what Brad 
was talking about.” Since joining, he’d been quiet and had put 
himself where he liked to be, in the background. “I just try to 
take in what people are saying, and listen to what everyone is 



complaining about,” he said. “I wish this or I wish that, and then 
bring it together and find the solution.” 

Brad knew little of Josh’s past — only that whatever Josh had 
done for the U.S. military sounded like the sort of thing he 
couldn’t talk about. “All I knew was that he was in a trailer in 
Afghanistan, working with generals,” said Brad. “When I tell 
him my problem — that I couldn’t see the data — he just says, ‘Hit 

Quietly, Josh had gone off and created for Brad pictures of 
the activity on IEX. Brad hit Refresh; the screen was now orga- 
nized in different shapes and colors. The strange 100-lot trades 
were suddenly bunched together and highlighted in useful ways: 
He could see patterns. And in the patterns he could see preda- 
tory activity neither he nor the investors had yet imagined. 

These new pictures showed him how the big Wall Street banks 
typically handled investors’ stock market orders. Here’s how it 
worked: Say you are a big investor — a mutual fund or a pension 
fund — and you have decided to make a big investment in Procter 
& Gamble. You are acting on behalf of a lot of ordinary Ameri- 
cans who have given you their savings to manage. You call some 
broker — Bank of America, say — and tell them you’d like to buy 
100,000 shares of Procter & Gamble. P&G’s shares are trading at, 
say, 82.95—82.97, with 1,000 shares listed on each side. You tell 
the big Wall Street bank you are willing to pay up to, say, $82.97 
a share. From that point on, you basically have no clue how your 
order — and the information it contains — is treated. Now Brad 
saw: The first thing the broker did was to ping IEX with an order 
to buy 100 shares, to see if IEX had a seller. This made total sense: 
You didn’t want to reveal you had a big buyer until you found a 
seller. What made a lot less sense was what many of the brokers 
did after they discovered the seller. They avoided him. 



Say, for example, that IEX actually had a seller waiting on 
it — a seller of 100,000 shares at $82.96. Instead of coming in 
and trying to buy a much bigger chunk of P&G, the big bank 
just kept pinging IEX with tiny 100-share orders — or the bank 
vanished entirely. If the bank had simply sent IEX an order to 
buy 100,000 shares of P&G at $82.97, the investor would have 
purchased all the shares he wanted without driving up the price. 
Instead, the bank had pinged away and — by revealing its insis- 
tent, noisy demand — goosed up the price of P&G’s stock, at the 
expense of the investor whose interests the bank was meant to 
represent. Adding to the injury, the bank typically wound up 
with only a fraction of the stock its customer wanted to buy. “It 
opened up this whole new realm of activity that was crazy to 
me,” Brad told his audience. It was as if the big Wall Street banks 
were looking to see if IEX had a big seller to avoid trading with 
him. “1 thought, Why the hell would anyone do this? All you 
do is increase the chances that an HFT will pick up your signal.” 

They didn’t all behave this way: A couple of the big banks 
followed up their 100-share orders by forking over the meat of 
the buy order, and executed the trade their customer had asked 
them to execute. (The Royal Bank of Canada was by far the 
best behaved.) But, in general, the big Wall Street banks who 
had connected to IEX — a group that in the first week of trading 
excluded Bank of America and Goldman Sachs — connected dis- 
ingenuously. It was as if they wished to appear to be interacting 
with the entire stock market, while actually they were trying to 
prevent any trades from happening outside their own dark pools. 

Brad now explained to the investors, who were of course pay- 
ing the price for this behavior, the reasons that the banks behaved 
as they did. The most obvious was to maximize the chance of 
executing the stock market orders given to them by investors in 



their own dark pools. The less honestly a bank looked for P&G 
stock outside of its own dark pool, the less likely it was to find it. 
This evasiveness explained the banks’ incredible ability to find, 
eventually, the other side of any trade inside their own dark 
pools. A bank that controlled less than 10 percent of all U.S. 
stock market orders was somehow able to satisfy more than half 
of its customers’ orders without ever leaving its own dark pool. 
Collectively, the banks had managed to move 38 percent of the 
entire U.S. stock market now traded inside their dark pools — 
and this is how they had done it. “It’s a facade that the market is 
interconnected,” said Brad. 

The big Wall Street banks wanted to trade in their own dark 
pools not only because they made more money — on top of their 
commissions — by selling the right to HFT to exploit orders 
inside their dark pools. They wanted to trade their orders inside 
their dark pools to boost the volumes in those pools, for appear- 
ances’ sake. The statistics used to measure the performance of 
the dark pools, as well as the performance of the public stock 
exchanges, were more than a little screwy. A stock market was 
judged by the volume of trading that occurred on it, and the 
nature of that volume. It was widely believed, for example, that 
the bigger the average trade size on an exchange, the better the 
market was for an investor. (By requiring fewer trades to com- 
plete his purchase or sale, the exchange reduced the likelihood 
of revealing an investor’s intentions to high-frequency traders.) 
Every dark pool and every stock exchange found ways to cook 
its own flattering statistics; the art of torturing data may never 
have been so finely practiced. For example, to show that they 
were capable of hosting big trades, the exchanges published the 
number of “block” trades of more than 10,000 shares they facil- 
itated. The New York Stock Exchange sent IEX a record of 



26 small trades it had made after IEX had routed an order to 
it — and then published the result on the ticker tape as a single 
15,000-share block. The dark pools were even worse, as no one 
but the banks that ran them had a clear view of what happened 
inside them. The banks all published their own self-generated 
stats on their own dark pools: Every bank ranked itself #1. “It’s 
an entire industry that overglorifies data, because data is so easy 
to game, and the true data is so hard to obtain,” said Brad. 

The banks did not merely manipulate the relevant statistics in 
their own dark pools; they often sought to undermine the stats 
of their competitors. That was another reason the banks were 
sending IEX orders in tiny 100-share lots: to lower the average 
trade size in a market that competed with the banks’ dark pools. 
A lower average trade size made IEX’s stats look bad — as if IEX 
were heavily populated by high-frequency traders. “When the 
customer goes to his broker and says, ‘What the hell happened? 
Why am I getting all these hundred-share fills?,’ his broker could 
easily say, ‘Well, I put the order on IEX,’ ” said Brad. The strat- 
egy cost their customers money, and the opportunity to buy and 
sell shares, but the customers wouldn’t know about it: All they 
would see was IEX’s average trade size falling. 

Soon after it opened for trading, IEX published its own sta- 
tistics — to describe, in a general way, what was happening in its 
market. “Since everyone is behaving in a particular way, you 
can’t see if anyone is behaving particularly badly,” said Brad. 
Now you could see. Despite the best efforts of Wall Street banks, 
the average size of IEX’s trades was by far the biggest of any 
stock exchange, public or private. More importantly, the trading 
that occurred was more random, unlinked to activity elsewhere 
in the stock market: For instance, the percentage of trades on 
IEX that followed the change in the price of some stock was 



half that of the other exchanges. (Investors were being picked 
off — as West Chester, Pennsylvania, money manager Rich 
Gates had been picked off — on exchanges that failed to move 
their standing orders quickly enough to keep up when stock 
prices changed.) Trades on IEX were also four times more likely 
than those elsewhere to trade at the midpoint between the cur- 
rent market bid and offer — which is to say, the price that most 
would agree was fair. Despite the reluctance of the big Wall 
Street banks to send them orders, the new exchange was already 
making the dark pools and public exchanges look bad, even by 
their own screwed-up standards.* 

Brad’s biggest weakness, as a strategist, was his inability to 
imagine just how badly others might behave. He had expected 
that the big banks would resist sending orders to IEX. He hadn’t 
imagined they would use their customers’ stock market orders 
to actively try at their customers’ expense to sabotage an exchange 
created to help their customers. “You want to create a system 
where behaving correctly would be rewarded,” he concluded. 
“And the system has been doing the opposite. It’s rational for a 
broker to behave badly.” 

The bad behavior played right into the hands of high- 
frequency traders in the most extraordinary ways. One day while 
watching the pictures Josh Blackburn had created for him. Brad 
saw a bank machine-gun IEX with 100-share lots and drive up 
a stock price 5 cents inside of 232 milliseconds. IEX’s delay — 
one-third of a millisecond — was of little use in disguising an 

* The Financial Industry Regulatory Authority (FINRA) publishes its own odd rank- 
ing of the public and private stock markets, based on how well they avoid breaking the 
law, presumably inadvertently, by trading outside the National Best Bid and Offer. In its 
first two months of trading, IEX ranked #1 on FINRA’s list. 



investor’s stock market order if a broker insisted on broadcasting 
a big order he controlled over a far longer period: HFT picked 
up the signal and was getting out in front of it. Wondering if 
the broker was spreading news of his buy order elsewhere, Brad 
turned his attention to the consolidated tape of all the trades 
that occurred in the U.S. stock market. “I just wondered: Is this 
broker peppering the whole Street, or is it just us?” he told the 
room full of investors. “What we found blew our minds.” 

For each trade on IEX, he’d spotted a nearly identical trade 
that had occurred at nearly the same time in some other mar- 
ket. “I noticed the odd trade sizes,” he said. He’d see a trade on 
IEX for 131 shares of, say, Procter & Gamble, and then he’d see, 
in some other market, exactly the same trade — 131 shares of 
Procter & Gamble — within a few milliseconds, but at a slightly 
different price. It happened over and over again. He also noticed 
that, in each case, on one side of the trade was a broker who had 
rented out his pipes to a high-frequency trader. 

Up till that point, most of the predation they had uncovered 
occurred when stock prices moved. A stock went up or down; 
the high-frequency guys found out before everyone else and 
took advantage of them. Roughly two-thirds of all stock market 
trades took place without moving the price of the stock— the 
trade happened at the seller’s offering price, or the buyer’s bid- 
ding price, or in between; afterwards, the bid and offering price 
remained the same as they had been before. What Brad now 
saw was how HFT, with the help of the banks, might exploit 
investors even when the stock price was stable. Say the market 
for Procter & Gamble’s shares was 80.50-80.52, and the quote 
was stable — the price wasn’t about to change. The National Best 
Bid was $80.50, and the National Best Offer was $80.52, and the 
stock was just sitting there. A seller of 10,000 Procter & Gamble 



shares appeared on IEX. IEX tried to price the orders that rested 
on it at the midpoint (the fair price), and so the 10,000 shares 
were being offered at $80.51. Some high-frequency trader would 
come into IEX — it was always a high-frequency trader — and 
chip away at the order: 131 shares here, 189 shares there. But else- 
where in the market, the same HFT was selling the shares — 131 
shares here, 189 shares there— at $80.52. On the surface, HFT 
was performing a useful function, building a bridge between 
buyer and seller. But the bridge was itself absurd. Why didn’t 
the broker who controlled the buy order simply come to IEX on 
behalf of his customer and buy, more cheaply, the shares offered? 

Back when Rich Gates conducted his experiments, he had 
managed to get himself robbed inside Wall Street’s dark pools, 
but only after he had changed the price of the stock (because the 
dark pools were so slow to move the price of his order resting 
inside of them). These trades that Brad was now noticing had 
happened without the market moving at all. He knew exactly 
why they were happening: The Wall Street banks were fail- 
ing to send their customers’ orders to the rest of the market- 
place. An investor had given a Wall Street bank an order, say, 
to buy 10,000 shares of P&G. The bank had sent it to its dark 
pool with instructions for the order to stay there, aggressively 
priced, at $80.52. The bank was boosting its dark pool stats — 
and also charging some HFT a fee rather than paying a fee to 
another exchange — but it was also ignoring whatever else was 
happening in the market. In a functional market, the inves- 
tors would simply have met in the middle and traded with each 
other at a price of $80.51. The price of the stock needn’t have 
moved a penny. The unnecessary price movement — caused by 
the screwed-up stock market— also played into HFT’s hands. 
Because high-frequency traders were always the first to detect 
any stock price movements, they were able to exploit, with other 



strategies, ordinary investors’ ignorance of the fact that the mar- 
ket price had changed. The original false note struck by the big 
Wall Street bank — the act of avoiding making trades outside of 
its own dark pool— became the prelude to a symphony of scalp- 
ing.* “We’re calling this ‘dark pool arbitrage,’ ” said Brad. 

IEX had built an exchange to eliminate the possibility of 
predatory trading — to prevent investors from being treated as 
prey. In the first two months of its existence, IEX had seen no 
activity from high-frequency traders except this. It was aston- 
ishing, when you stopped to think about it, how aggressively 
capitalism protected its financial middleman, even when he was 
totally unnecessary. Almost magically, the banks had generated 
the need for financial intermediation — to compensate for their 
own unwillingness to do the job honestly. 

Brad opened the floor for questions. For the first few minutes, 
the investors vied with each other to see who could best control 
his anger and exhibit the sort of measured behavior investors are 
famous for. 

“Do you think of HFT differently than you did before you 
opened?” asked one. 

That question might have been better answered by Ronan, 
who had just returned from a tour of the big HFT firms, and 
now leaned against a wall on the side of the room. Brad had asked 
Ronan to explain to the investors the technical end of things — 

* The reader might question the characterization of such small-time skimming as scalp- 
ing. But a penny here, a penny there adds up in the most extraordinary ways in the 
U.S. stock market. At IEX, the Puzzle Masters made a quick-and-dirty calculation of 
the likely profits made annually by HFT from dark pool arbitrage. They added up all 
its instances over a fifteen-day period, then came up with a number: The haul for HFT 
from the U.S. stock market alone came to more than a billion dollars a year. And this 
was just a single trading strategy. “They’ve been in business for ten weeks and they’ve 
now found four of these strategies,” said one big investor of IEX. “Who knows how 
many more they’ll find?” A billion here, a billion there: It adds up. 



how IEX had created its 350-microsecond delay, the magic shoe- 
box, and so on — and to relate the details of his tour. He’d done 
it. But on the subject of HFT he held himself back. To speak his 
mind, Ronan needed to feel like himself, which, imprisoned in 
a gray suit and addressing a semiformal audience, he clearly did 
not. Put another way: It was just extremely difficult for Ronan 
to say what he felt without using the word “fuck.” Watching 
him string together sentences without profanity was like watch- 
ing someone try to swim across a river without using his arms or 
his legs. Curiously, he later admitted, he wasn’t worried that the 
audience would be offended by bad language. “It was because 
some of them want to be the alpha male cursing in the room,” 
he said. “When I say ‘fuck,’ they think I’m stealing the show — 
so when I’m in front of a group I go as straight as I can.” 

“I hate them a lot less than before we started,” said Brad. 
“This is not their fault. I think most of them have just rational- 
ized that the market is creating the inefficiencies and they are 
just capitalizing on them. Really, it’s brilliant what they have 
done within the bounds of the regulation. They are much less of 
a villain than I thought. The system has let down the investor.” 

A forgiving sentiment. But at that moment the investors in 
the conference room did not seem in a forgiving mood. “It’s still 
shocking to me to see how the banks are colluding against us,” 
one of the investors later said. “It shows everyone is a bad actor. 
And then when you add in that you ask them to route to IEX 
and they refuse, it’s even worse. Even though I had heard some 
of it before, I was still incensed. If that was the first time I was 
hearing it, I think I’d have gone bonkers.” 

An investor raised his hand and motioned to some numbers 
Brad had scribbled on a whiteboard to illustrate how a particular 
bank had enabled dark pool arbitrage. 

“Who is that?” he asked, and not calmly. 



An uneasy look crossed Brad’s face. He was now hearing that 
question more and more. Just that morning, an outraged inves- 
tor listening to a dry run of his presentation had stopped him to 
ask: “Which bank is the worst?” “I can’t tell you,” he said, and 
explained that the agreements the big Wall Street banks signed 
with IEX forbade IEX from speaking about any bank without 
its permission. 

“Do you know how frustrating it is to sit here and hear this 
and not know who that broker is?” said another investor. 

It wasn’t easy being Brad Katsuyama — to try to effect some 
practical change without a great deal of fuss, when the change in 
question was, when you got right down to it, a radical overhaul 
of a social order. Brad was not by nature a radical. He was simply 
in possession of radical truths. 

“What we want to do is highlight the good brokers,” said 
Brad. “We need the brokers who are doing the right thing to get 
rewarded.” That was the only way around the problem. Brad had 
asked for the banks’ permission to highlight the virtue of the ones 
that behaved relatively well, and they had granted it. “Speaking 
about someone in a positive light does not violate the terms of not 
speaking about someone in a negative light,” he said. 

The audience considered this. 

“How many good brokers are there?” asked an investor at 

“Ten,” said Brad. (IEX had dealings with ninety-four.) The 
ten included the Royal Bank of Canada, Sanford Bernstein, and 
a bunch of even smaller outfits. “Three are meaningful,” he 
added. Morgan Stanley, J.P. Morgan, and Goldman Sachs. 

“Why would any broker behave well?” 

“The long-term benefit is that when the shit hits the fan, it 
will quickly become clear who made good decisions and who 
made bad decisions,” said Brad. 



He wondered, often, what it would look like if and when 
the shit in question hit the fan: The stock market at bottom was 
rigged. The icon of global capitalism was a fraud. How would 
enterprising politicians and plaintiffs’ lawyers and state attorneys 
general respond to that news? The thought of it actually didn’t 
give him all that much pleasure. Really, he just wanted to fix 
the problem. At some level, he still didn’t understand why Wall 
Street banks needed to make his task so difficult. 

“Is there a concern from you that the publicity will create 
even more hostility?” asked another. He wanted to know if tell- 
ing the world who the good brokers were would make the bad 
ones worse. 

“The bad brokers can’t try harder at being bad,” said Brad. 
“Some of these brokers are doing everything they can not to do 
what the client wants them to do.” 

An investor wanted to return to the scribbled numbers that 
illustrated how one particular bank had enabled dark pool arbi- 
trage. “So what do these guys say when you show them that? 

“Some of them say, ‘You’re one hundred percent right,”’ 
said Brad. “ ‘This shit happens.’ One even said, ‘We used to sit 
around all the time talking about how to fuck up other people’s 
dark pools.’ Some of them say, ‘I have no idea what you’re talk- 
ing about. We have heuristic data bullshit and other mumbo 
jumbo to determine our routing.’ ” 

“That’s a technical term — ‘heuristic data bullshit and other 
mumbo jumbo’?” an investor asked. A few guys laughed. 

Technology had collided with Wall Street in a peculiar way. 
It had been used, as it should have been used, to increase effi- 
ciency. But it had also been used to introduce a peculiar sort 
of market inefficiency. This new inefficiency was not like the 
inefficiencies that financial markets can easily correct. After a 



big buyer enters the market and drives up the price of Brent 
crude oil, for example, it’s healthy and good when speculators 
jump in and drive up the price of North Texas crude, too. It’s 
healthy and good when traders see the relationship between the 
price of crude oil and the price of oil company stocks, and drive 
these stocks higher. It’s even healthy and good when some clever 
high-frequency trader divines a necessary statistical relationship 
between the share prices of Chevron and Exxon, and responds 
when it gets out of whack. It was neither healthy nor good when 
public stock exchanges introduced order types and speed advan- 
tages that high-frequency traders could use to exploit everyone 
else. This sort of inefficiency didn’t vanish the moment it was 
spotted and acted upon. It was like a broken slot machine in the 
casino that pays off every time. It would keep paying off until 
someone said something about it; but no one who played the 
slot machine had any interest in pointing out that it was broken. 

Some large amount of what Wall Street had done with tech- 
nology had been done simply so that someone inside the financial 
markets would know something that the outside world did not. 
The same system that once gave us subprime mortgage collater- 
alized debt obligations no investor could possibly truly under- 
stand now gave us stock market trades that occurred at fractions 
of a penny at unsafe speeds using order types that no investor 
could possibly truly understand. That is why Brad Katsuyama’s 
most distinctive trait — his desire to explain things not so he 
would be understood but so that others would understand — was 
so seditious. He attacked the newly automated financial system 
at its core: the money it made from its incomprehensibility. 

Another investor, silent till that point, now raised his hand. 
“It seems like there’s a first mover risk for someone to behave 
the right way,” he said. He was right: Even the banks that were 



behaving relatively well weren’t behaving all that well. A big 
Wall Street bank that gave IEX an honest shot to execute its 
customers’ orders would suffer a collapse in its dark pool trad- 
ing, and in its profits. The bad banks would pounce on the good 
bank and argue that, because its dark pool was worse than all the 
others, it shouldn’t be given the orders in the first place. That, 
Brad told the investors, had been maybe his biggest concern. 
Would any big Wall Street bank have the ability to see a few 
years down the road, and summon the nerve to go first? Then 
he clicked on a slide. On top it read: December 19, 2013. 

YOU COULD NEVER say for sure exactly what was going on inside 
one of the big Wall Street banks, but it was a mistake to think of 
a bank as a coherent entity. They were fractious, and intensely 
political. Most everyone might be thinking mainly about his 
year-end bonus, but that didn’t mean there wasn’t one person 
who wasn’t, and it certainly didn’t mean that everyone inside a 
big bank shared the same incentives. A dollar in one guy’s pocket 
was, in some places, a dollar out of another’s. For instance, the 
guys in the prop group who traded against the firm’s custom- 
ers in the dark pool would naturally feel a different concern for 
those customers than the guy whose job it was to sell them stuff 
would — if for no other reason than that it is harder to rip off a 
person when you actually need to see him, face to face. That’s 
why the banks kept the prop traders on different floors from the 
salespeople, often in entirely different buildings. It wasn’t simply 
to please the regulators; all involved would prefer that there be 
no conversation between the two groups. The customer guy was 
better at his job — and had deniability — if he remained oblivi- 
ous to whatever the prop guy was up to. The frantic stupidity 



of Wall Street’s stock order routers and algorithms was simply 
an extension into the computer of the willful ignorance of its 

Brad’s job, as he saw it, was to force the argument between 
the salespeople and the prop people — and to arm the salespeople 
with a really great argument, which included the distinct pos- 
sibility that investors in the stock market were about to wake 
up to what was being done to them, and go to war against the 
people who were doing it. In most cases, he had no idea if he had 
succeeded and, as a result, suspected he had not. 

Right from the start, the view from inside Goldman Sachs had 
been less cluttered than the view from inside the other big Wall 
Street banks. Goldman was unlike the other banks; for instance, 
the first thing the people he met at the other banks usually did 
was tell him of the hostility all the other banks felt toward IEX, 
and of the nefariousness of the other banks’ dark pools. Goldman 
was aloof, and didn’t appear to care what its competitors were 
saying or thinking about IEX. In their stock market trading and 
perhaps in other departments as well, Goldman was undergoing 
some kind of transition. In February 2013, its head of electronic 
trading, Greg Tusar, had left to work for Getco, the big high- 
frequency trading firm. The two partners then assigned to figure 
out Goldman’s role in the global stock markets — Ron Morgan 
and Brian Levine — were not high-frequency trading types. 
They didn’t bear a great deal of responsibility for whatever the 
high-frequency trading types had done before they took over. 
Morgan worked in New York and was in charge of sales; Levine, 
responsible for trading, worked in London. Both were apparently 
worried about what they had found when they stepped into their 
new positions. Brad knew this because, oddly, Ron Morgan had 
called him. “He found us by talking to clients about what they 



wanted,” said Brad. A week after they first met, Morgan invited 
Brad back to meet with a group of even more senior executives. 
“That didn’t happen anywhere else,” Brad said. After he left, he 
was told that the ensuing discussion had reached “the highest 
levels of the firm.” 

In taking over, Morgan and Levine had been tasked with 
answering a big question posed by the people who ran Gold- 
man Sachs: Why was Morgan Stanley growing so fast? Their 
rival s market share was booming, while Goldman’s was stag- 
nant. Levine and Morgan did what everyone on Wall Street 
did when they wanted to find out what was going on inside a 
rival bank: They invited some of its employees in for job inter- 
views. The Morgan Stanley employees explained to them that 
the firm was now trading 300 million shares a day — 30 percent 
of the volume of the New York Stock Exchange — through what 
it called “Speedway.” Speedway was a service Morgan Stanley 
provided to high-frequency traders. Morgan Stanley built a 
high-frequency trading infrastructure — co-location at various 
exchanges, the fastest routes between them, a straight road into 
the bank s dark pool and so on — and then turned around and 
leased their facilities to the smaller HFT firms, which couldn’t 
afford the up-front cost of building their own systems. Mor- 
gan Stanley got credit for, and commissions from, everything 
the HFT guys did inside Morgan Stanley’s pipes. The Morgan 
Stanley employees angling for jobs at Goldman Sachs told the 
Goldman executives that Speedway was now making Morgan 
Stanley $500 million a year, and that it was growing. This raised 
the obvious question for Goldman Sachs: Should we create our 
own Speedway? Should we further embrace high-frequency 

One of Goldman’s clients handed Ronnie Morgan a list of 



thirty-three big investors to whom he should speak before 
making this decision. This client didn’t know if Morgan had 
spoken to people beyond this list, but he confirmed for him- 
self that Morgan had spoken to each of the thirty-three people 
individually. At the same time, Morgan and Levine began to 
ask some obvious questions about Goldman Sachs’s stock mar- 
ket businesses. Could Goldman ever be as fast or as smart as 
the more nimble high-frequency trading firms? Why, if Gold- 
man only controlled 8 percent of all stock market orders, was it 
able to trade more than a third of those orders in its own dark 
pool? Given how little of the flow Goldman saw, what was the 
likelihood that the best price for an investor’s order came from 
some other Goldman customer? How did Wall Street dark pools 
interact with each other and with the exchanges? How stable 
was this increasingly complex financial market? Was it a good 
thing that the U.S. stock market model had been exported to 
other countries and other financial markets? 

They already knew or could guess most of the answers; for 
the questions still hanging, the investors pointed them toward 
an unusually forthright and knowledgeable guy they knew and 
trusted who was starting a new stock exchange: Brad Katsuyama. 

What struck Brad about his visit to Goldman Sachs was not 
only that Levine and Morgan were willing to spend time with 
him, but that they took the ideas from their conversations to 
their superiors. Levine seemed particularly concerned about the 
stock market’s instability. “Unless there are some changes, there’s 
going to be a massive crash,” he said, “a flash crash times ten.” In 
conversation and in presentations, he impressed the point upon 
Goldman’s top executives, and also asked, “Do you really need 
the only differentiator in the market to be speed? Because that’s 
what it seems to be.” It wasn’t all that hard for the people who 



ran Goldman Sachs to see the source of the problem, or to see 
why no one inside the system cared to point it out. “There’s no 
upside in it — that’s why no one ever steps out on it,” said Levine. 
“And everyone’s got career risk. And no one is thinking that far 
ahead. They are looking at the next paycheck.” 

A long string of myopic decisions had created new risks in the 
U.S. stock market. Its complexity was just one manifestation of 
the problem, but in it, the Goldman partners both felt sure, lay 
some future calamity. The sensational technical glitches weren’t 
anomalies but symptoms. And a stock market calamity, Ron 
Morgan and Brian Levine both thought, would end up being 
blamed generally on the big Wall Street banks, and specifically 
on Goldman Sachs. Goldman earned $7 billion a year from its 
equity business; that business would be put at risk by any crisis. 

But it was more than that. At forty-eight and forty-three, 
respectively, Morgan and Levine were, by Wall Street standards, 
old guys. Morgan had been made a Goldman partner back in 
2004, Levine in 2006. Both confided to friends that IEX pre- 
sented them with a choice, at what might be a pivotal financial 
historical moment. An investor who knew Ron Morgan said, 
“Ronnie’s saying to himself, ‘You work for twenty-five years in 
the business, how often do you have a chance to make a differ- 
ence?’ ” Brian Levine himself said, “I think it’s a business deci- 
sion. I also think it’s a moral decision. I think this is the shot we 
have. And I think Brad is the right guy. It’s the best odds we 
have to fix the problem.” 

BEFORE THEY OPENED their market, on October 25, 2013, the 
thirty-two employees of IEX made private guesses as to how 
many shares they’d trade their first day and in their first week. 



The median of the estimates came in at 159,500 shares the first 
day and 2.5 million shares the first week. The lowest estimate 
came from Matt Trudeau, the only one of them who had ever 
built a new stock market from scratch: 2,500 shares for the first 
day and 100,000 for the week. Of the ninety-four stock broker- 
age firms in various stages of agreeing to connect to IEX, most 
of them small outfits, only about fifteen were ready on the first 
day. “Brokers are telling their clients they’re connected, but we 
haven’t even gotten their paperwork,” said Brad. When asked 
how big the exchange might be at the end of the first year, Brad 
guessed, or perhaps hoped, that it would trade between 40 and 
50 million shares a day. 

To cover their running costs, they needed to trade about 50 
million shares a day. If they failed to cover their running costs, 
there was a question of how long they could last. “It’s binary,” 
said Don Bollerman. “Either we are a resounding success or 
we are a complete flop. We’re done in six to twelve months. In 
twelve months I know whether I need to look for a job.” Brad 
thought that their bid to create an example of a fair financial 
market — and maybe change Wall Street’s culture — could take 
longer and prove messier. He expected their first year to feel 
more like nineteenth-century trench warfare than a twenty- 
first-century drone strike. “We’re just collecting data,” he said. 
“You cannot make a case without data. And you don’t have data 
unless you have trades.” Even Brad agreed: “It’s over when we 
run out of money.” 

On the first day, they traded 568,524 shares. Most of the vol- 
ume came from regional brokerage firms and Wall Street brokers 
that had no dark pools — the Royal Bank of Canada and San- 
ford Bernstein. Their first week, they traded a bit over 12 million 
shares. Each week after that, they grew slightly, until, in the third 



week of December, they were trading roughly 50 million shares 
each week. On Wednesday, December 18, they traded 11,827,232 
shares. By then Goldman Sachs had connected to IEX, but its 
orders were arriving on the new exchange in the same untrust- 
ing spirit as those from the other big Wall Street banks: in tiny lot 
sizes, resting for just a few milliseconds, then leaving. 

The first different-looking stock market order sent by Gold- 
man to IEX landed on December 19, 2013, at 3:09:42 p.m. 662 
milliseconds, 361 microseconds, and 406 nanoseconds. Anyone 
who had been in IEX’s one-room office when it arrived would 
have known that something unusual was happening. The com- 
puter screens jitterbugged as the information flowed into the 
market in an entirely new way. One by one, the employees arose 
from their chairs; a few minutes into the surge, all but Zoran 
Perkov were on their feet. Then they began to shout. 

“Were at fifteen million!” someone yelled, ten minutes into 
the surge. In the previous 331 minutes they had traded roughly 
5 million shares. 

“Twenty million!” 

“Fucking Goldman Sachs!” 

“Thirty million!” 

The enthusiasm was unpracticed, almost unnatural. It was as 
if an oil well had gushed up through the floor during a meeting 
of the chess club. 

“We just passed AMEX,” shouted John Schwall, referring to 
the American Stock Exchange. “We’re ahead of AMEX in mar- 
ket share.” 

“And we gave them a one-hundred-and-twenty-year head 
start,” said Ronan, playing a little loose with history. Some- 
one had given Ronan a $300 bottle of Champagne. He’d told 
Schwall that it had cost only forty bucks, because Schwall didn’t 



want anyone inside IEX accepting gifts of more than forty bucks 
from anyone outside of it. Now Ronan fished the contraband 
from under his desk and found some paper cups. 

Someone else put down a phone and said, “That was J.R 
Morgan, asking, ‘What just happened?’ They say they may have 
to do something.” 

Don put down his phone. “That was Goldman. They say they 
aren’t even big. They’re coming big tomorrow.” 

“Forty million!” 

At his desk Zoran sat calmly, watching traffic patterns. “Don’t 
tell anyone, but we’re still bored,” he said. “This is nothing.” 

Fifty-one minutes after Goldman Sachs had given them their 
first honest shot at Wall Street customers’ stock market orders, 
the U.S. stock market closed. Brad walked off the floor and into 
a small office, enclosed by glass. He thought through what had 
just happened. “We needed one person to buy in and say, ‘You’re 
right,’ ” he said. “It means that Goldman Sachs agrees with us.” 
Then he thought some more. Goldman Sachs wasn’t a single 
entity; it was a bunch of people who didn’t always agree with 
each other. Two of these people had been given a new authority, 
and they had used it to take a different, longer-term approach 
than anyone imagined Goldman Sachs was capable of. These 
two people made all the difference. “I got lucky Brian is Brian 
and Ronnie is Ronnie,” said Brad. “This is because of them. 
Now the others can’t ignore this. They can’t marginalize it.” 
Then he blinked. “I could fucking cry now,” he said. 

He’d just been given a glimpse of the future — he felt certain 
of it. Goldman Sachs was insisting that the U.S. stock market 
needed to change, and that IEX was the place to change it. If 
Goldman Sachs was willing to acknowledge to investors that 
this new market was the best chance for fairness and stability, 



the other banks would be pressured to follow. The more orders 
that flowed onto IEX, the better the experience for investors, 
and the harder it would be for the banks to evade this new, fair 
market. At that moment, as Goldman’s orders flowed onto IEX, 
the stock market felt a bit like a river that wanted to jump its 
banks. All that had been needed was for one man with a shovel 
to dig a trench in an existing levee, and the pressure from the 
water would finish the job — which was why men caught dig- 
ging into the banks on certain stretches of the Mississippi River 
were once shot on sight. Brad Katsuyama was the man with the 
shovel, positioned at the river’s most vulnerable bend. Goldman 
had arrived, with explosives, to help him. 

Three weeks later, he stood before a group of investors who, 
if they acted together, might force change upon Wall Street. 
To show them that change was possible, he flashed on a big 
screen the data from what had happened, for fifty-one minutes, 
on December 19. The data showed, among other things, the 
power of trust. Goldman had actually sent more orders to IEX 
the day before, on December 18. So much more had traded on 
December 19 because, on that day, for just fifty-one minutes, 
Goldman had entrusted them with most of its orders for ten 
seconds or more. That trust had been rewarded: The market felt 
fair; 92 percent of those orders traded at the midpoint — the fan- 
price — compared to 17 percent that traded at the midpoint in 
Wall Street’s dark pools. (The number on the public exchanges 
was even lower.) Their average trade size was twice the market 
average, despite the efforts of other Wall Street banks to under- 
mine them. 

IEX represented a choice. IEX also made a point: that this 
market which had become intentionally and overly complicated 
might be understood. That, to function properly, a free finan- 



cial market didn’t need to be rigged in someone’s favor. It didn’t 
need in some sick way the kickbacks, and payment for order 
flow, and co-location, and all sorts of unfair advantages handed 
to a small handful of traders. All it needed was for the men in 
the room and other investors like them to take responsibility for 
understanding it, and then to seize its controls. “The backbone 
of the market is investors coming together to trade,” said Brad. 

When he was finished, an investor raised his hand. “They did 
it on December nineteenth,” he asked. “And then what?” 



T he trial of Sergey Aleynikov ran for ten days in Decem- 
ber of 2010 and was notable for its paucity of informed 
outsiders. High-frequency trading was a small world, and 
the people who did it, or knew anything at all about it, appar- 
ently had far less interest in testifying at trials than in mak- 
ing their personal fortunes. The one outside expert witness on 
the subject called by the government was an assistant professor 
of finance at Illinois Institute of Technology named Benja- 
min Van Vliet. Van Vliet had become an expert in response to 
journalists’ need for one. While teaching a computer coding 
course, he’d cast around for something sexy for the students 
to program, and landed on high-frequency trading platforms. 
In mid-2010, Forbes magazine called him out of the blue to 
ask him what he thought about a fiber-optic cable that Spread 
Networks had strung from Chicago to New Jersey. Van Vliet 
had never heard of Spread Networks, and knew nothing about 
the cable, but wound up with his name in print — which, of 
course, led to more calls from journalists, who needed a high- 



frequency trading expert. Then came the flash crash, and Van 
Vliet’s phone rang off the hook. Eventually, federal prosecutors 
found him and asked him to serve as their expert witness in the 
trial of a former Goldman Sachs high-frequency programmer. 
Van Vliet still had never actually done any high-frequency 
trading himself, and had little to add on the value or the gist of 
what Serge Aleynikov had taken from Goldman Sachs. About 
the market itself he was badly misinformed. (He described 
Goldman Sachs as “the New York Yankees” of high-frequency 
trading.) He turned out to have testified as an expert witness 
in an earlier trial involving the theft of high-frequency trading 
code, after which the judge in the case said that the idea that a 
high-frequency trading program was some kind of science was 
“utter baloney.” 

The jury in Sergey Aleynikov’s trial consisted mainly of high 
school graduates; all of the jurors lacked experience program- 
ming computers. “They would bring my computer into the court- 
room,” recalled Serge incredulously. “They would pull out the 
hard drive and show it to the jury. As evidence!” Save for Misha 
Malyshev, Serge’s onetime employer, the people who took the 
stand had no credible knowledge of high-frequency trading: 
how the money got made, what sort of computer code was valu- 
able, and so on. Malyshev testified as a witness for the prosecution 
that Goldman’s code was of no use whatsoever in the system 
he’d hired Serge to build — Goldman’s code was written in a 
different programming language, it was slow and clunky, it had 
been designed for a firm that was trading with its own custom- 
ers, and Teza, Malyshev’s firm, didn’t have customers, and so 
on — but when he looked over, he saw that half the jury appeared 
to be sleeping. “If I were a juror, and I wasn’t a programmer,” 
said Serge, “it would be very difficult for me to understand why 
I did what I did.” 



Goldman Sachs’s role in the trial was to make genuine under- 
standing even more difficult. Its employees, on the witness stand, 
behaved more like salesmen for the prosecution than citizens 
of the state. “It’s not that they lied,” said Serge. “But they told 
things that were not in their expertise.” When his former boss, 
Adam Schlesinger, was asked about the code, he said that every- 
thing at Goldman was proprietary. “I wouldn’t say he lied, but he 
was talking about stuff that he did not understand, and so he was 
misunderstood,” said Serge. 

Our system of justice is a poor tool for digging out a rich 
truth. What was really needed, it seemed to me, was for Serge 
Aleynikov to be forced to explain what he had done, and why, 
to people able to understand the explanation and judge it. 
Goldman Sachs had never asked him to explain himself, and 
the FBI had not sought help from anyone who actually knew 
anything at all about computers or the high-frequency trad- 
ing business. And so over two nights, in a private room of a 
Wall Street restaurant, I convened a kind of second trial. To 
serve as both jury and prosecution, I invited half a dozen people 
intimately familiar with Goldman Sachs, high-frequency trad- 
ing, and computer programming. All were authorities on our 
abstruse new stock market; several had written high-frequency 
code; one had actually developed software for Goldman’s high- 
frequency traders. All were men. They’d grown up in four dif- 
ferent countries between them, but all now lived in the United 
States. All of them worked on Wall Street, and so, to express 
themselves freely, they needed to remain anonymous. Among 
them were employees of IEX. 

All were naturally skeptical — of both Goldman Sachs and 
Serge Aleynikov. They assumed that if Serge had been sentenced 
to eight years in jail he must have done something wrong. They 



just hadn’t bothered to figure out what that was. All of them 
had followed the case in the newspapers and noted the shiver it 
had sent through the spines of Wall Street’s software developers. 
Until Serge was sent to jail for doing it, it was common practice 
for Wall Street programmers to take code they had worked on 
when they left for new jobs. “A guy got put in jail for taking 
something no one understood,” as one of Serge’s new jurors put 
it. “Every tech programmer out there got the message: Take 
code and you could go to jail. It was huge.” The arrest of Serge 
Aleynikov had also caused a lot of people, for the first time, to 
begin to use the phrase “high-frequency trading.” Another new 
juror, who in 2009 had worked for a big Wall Street bank, said, 
“When he was arrested, we had a meeting for all the electronic 
trading personnel, to talk about a one-pager they’d drafted to be 
discussed with their clients around this new topic called ‘high- 
frequency trading.’ ” 

The restaurant was one of those old-school Wall Street places 
that charge you a thousand bucks for a private room and then 
more or less challenge you to eat your way back to even. Food 
and drink arrived in massive quantities: vast platters of lobster 
and crab, steaks the size of desktop computer screens, smok- 
ing mountains of potatoes and spinach. It was the sort of meal 
cooked decades ago, for traders who spent their days trusting 
their gut and their nights rewarding it; but this monstrous feast 
was now being served to a collection of weedy technologists, 
the people who controlled the machines that now controlled 
the markets, and who had, in the bargain, put the old school 
out of business. They sat around the table staring at the piles 
of food, like a conquering army of eunuchs who had stumbled 
into the harem of their enemy. At any rate, they made hardly a 
dent. Serge, for his part, ate so little, and with such disinterest, 



that I half expected him to lift off his chair and float up to the 

His new jurors began, interestingly, by asking him lots of per- 
sonal questions. They wanted to figure out what kind of guy he 
was. They took an interest, for example, in his job-market his- 
tory, and noted that his behavior was pretty consistently that of 
a geek who had more interest in his work than in the money the 
work generated. They established fairly quickly — how, I do not 
know — that he was not just smart but seriously gifted. “These 
guys are usually smart in one small area,” one of them later 
explained to me. “For a technologist to be so totally dominant 
in so many areas is just really, really unusual.” 

They then began to probe his career at Goldman Sachs. They 
were surprised to learn that he had “super-user status” inside 
Goldman, which is to say he was one of a handful of people 
(roughly 35, in a firm that then had more than 31,000 employ- 
ees) who could log onto the system as an administrator. Such 
privileged access would have enabled him, at any time, to buy a 
cheap USB flash drive, plug it into his terminal, and take all of 
Goldman’s computer code without anyone having any idea that 
he had done it. That fact alone didn’t prove anything to them. As 
one pointed out to Serge directly, lots of thieves are sloppy and 
careless; just because he was sloppy and careless didn’t mean he 
was not a thief. On the other hand, they all agreed, there wasn’t 
anything the least bit suspicious, much less nefarious, about the 
manner in which he had taken what he had taken. Using a sub- 
version repository to store code and deleting one’s bash history 
were common practices. The latter made a great deal of sense if 
you typed your passwords into command lines. In short, Serge 
had not behaved like a man trying to cover his tracks. One of his 
new jurors stated the obvious: “If deleting the bash history was 



so clever and devious, why had Goldman ever found out he’d 
taken anything?” 

To these new jurors, the story that the FBI found so uncon- 
vincing — that Serge had taken the files because he thought 
he might later like to parse the open source code contained 
within — made a lot of sense. As Goldman hadn’t permitted him 
to release his debugged or improved code back to the public — 
even though the original free license often stated that improve- 
ments must be publicly shared — the only way for him to get his 
hands on these files was to take the Goldman code. That he had 
also taken some code that wasn’t open source, which happened 
to be in the same files as the open source code, surprised no 
one. Grabbing a bunch of files that contained both open source 
and non-open source code was an efficient way for him to col- 
lect the open source code, even if the open source code was 
the only code that interested him. It would have made far less 
sense for him to hunt around the Internet for the open source 
code he wanted, as it was scattered all over cyberspace. It was 
also entirely plausible to them that Serge’s interest was confined 
to the open source code, because that was the general-purpose 
code that might be repurposed later. The Goldman proprietary 
code was written specifically for Goldman’s platform; it would 
have been of little use in any new system he wished to build. 
(The two small pieces of code Serge had sent into Teza’s com- 
puters before his arrest both came with open source licenses.) 
“Even if he had taken Goldman’s whole platform, it would have 
been faster and better for him to write the new platform him- 
self,” said one juror. 

Several times Serge surprised the jurors with his answers. 
They were all shocked, for instance, that from the day Serge 
first arrived at Goldman, he had been able to send Goldman’s 



source code to himself weekly, without anyone at Goldman say- 
ing a word to him about it. “At Citadel, if you stick a USB drive 
into your work station, someone is standing next to you within 
five minutes, asking you what the hell you are doing,” said a 
juror who had worked there. Most were surprised by how little 
Serge had taken in relation to the whole: eight megabytes, in a 
platform that consisted of nearly fifteen hundred megabytes of 
code. The most cynical among them were surprised mostly by 
what he had not taken. 

“Did you take the strats?” asked one, referring to Goldman’s 
high-frequency trading strategies. 

“No,” said Serge. That was one thing the prosecutors hadn’t 
accused him of. 

“But that’s the secret sauce, if there is one,” said the juror. “If 
you’re going to take something, take the strats.” 

“I wasn’t interested in the strats,” said Serge. 

“But that’s like stealing the jewelry box without the jewels,” 
said another juror. 

“You had super-user status!” said the first. “You could easily 
have taken the strats. Why didn’t you?” 

“To me, the technology really is more interesting than the 
strats,” said Serge. 

“You weren’t interested in how they made hundreds of mil- 
lions of dollars?” asked someone else. 

“Not really,” said Serge. “It’s all one big gamble, one way or 

Because they had seen it before in other programmer types, 
they were not totally shocked by his indifference to Goldman’s 
trading, or by how far Goldman had kept him from the action. 
Talking to a programmer type about the trading business was a 
bit like talking to the house plumber at work in the basement 



about the card game the Mafia don was running upstairs. “He 
knew so little about the business context,” one of the jurors said, 
after attending both dinners. “You’d have to try to know as little 
as he did.” Another said, “He knew as much as they wanted him 
to know about how they made money, which was virtually noth- 
ing. He wasn’t there for very long. He came in with no context. 
And he spent all of his time troubleshooting.” Another said he had 
found Serge to be the epitome of the programmer whose value 
the big Wall Street banks tried to minimize — by using their skills 
without fully admitting them into the business. “You see two 
resumes from the banks,” he said. “You line them up on paper 
and say maybe there’s a ten percent difference between them. But 
one guy is getting paid three hundred grand and the other is get- 
ting one point five million. The difference is one guy has been 
given the big picture, and the other hasn’t.” Serge had never been 
shown the big picture. Still, it was obvious to the jurors — even 
if it wasn’t to Serge — why Goldman had hired him when it had. 
With the introduction of Reg NMS in 2007, the speed of any 
financial intermediary’s trading system became its most important 
attribute: the speed with which it took in market data and the 
speed with which it responded to that data. “Whether he knew it 
or not,” said one juror, “he was hired to build Goldman’s view of 
the market. No Reg NMS, no Serge in finance.” 

At least some part of the reason he remained oblivious to the 
nature of Goldman Sachs’s trading business, all of the jurors 
noticed, was that his heart was elsewhere. “I think passion plays 
a big role,” said a juror who himself had spent his entire career 
writing code. “The moment he started talking about coding, 
his eyes lit up.” Another added, “The fact that he kept trying to 
work on open source shit even while he was at Goldman says 
something about the guy.” 



They didn’t all agree that what Serge had taken had no value, 
either to him or to Goldman. But what value it might have had 
in creating a new system would have been trivial and indirect. 
“I can guarantee you this: He did not steal code to use it on 
some other system,” one said, and none of the others disagreed. 
For my part, I didn’t fully understand why some parts of Gold- 
man’s system might not be useful in some other system. “Gold- 
man’s code base is like buying a really old house,” one of the 
jurors explained. “And you take the trouble to soup it up. But 
it still has the problems of a really old house. Teza was going 
to build a new house, on new land. Why would you take one- 
hundred-year-old copper pipes and put them in my new house? 
It isn’t that they couldn’t be used; it’s that the amount of trouble 
involved in making it useful is ridiculous.” A third added, “It’s 
way easier to start from scratch.” Their conviction that Gold- 
man’s code was not terribly useful outside of Goldman grew 
even stronger when they learned — later, as Serge failed to men- 
tion it at the dinners — that the new system Serge planned to 
create was to be written in a different computer language than 
the Goldman code. 

The perplexing question, at least to me, was why Serge had 
taken anything. A full month after he’d left Goldman Sachs, he 
still had not touched the code he had taken. If the code was so 
unimportant to him that he didn’t bother to open it up and study 
it; if most of it was either so clunky or so peculiar to Goldman’s 
system that it was next to useless outside Goldman — why take it? 
Oddly, his jurors didn’t find this hard to understand. One put it 
this way: “If Person A steals a bike from Person B, then Person 
A is riding a bike to school, and Person B is walking. Person A is 
better off at the expense of Person B. That is clear-cut, and most 
people’s view of theft. 



“In Serge’s case, think of being at a company for three years, 
and you carry a spiral notebook and write everything down. 
Everything about your meetings, your ideas, products, sales, cli- 
ent meetings — it’s all written down in that notebook. You leave 
for your new job and take the notebook with you — as most 
people do. The contents of your notebook relate to your history 
at the prior company but have very little relevance to your new 
job. You may never look at it again. Maybe there are some ideas, 
or templates, or thoughts you can draw on. But that notebook 
is related to your prior job, and you will start a new notebook 
at your new job which will make the old one irrelevant. . . . 
For programmers, their code is their spiral notebook. [It enables 
them] to remember what they worked on — but it has very little 
relevance to what they will build next. . . . He took a spiral note- 
book that had very little relevance outside of Goldman Sachs.” 

To the well-informed jury, the real mystery wasn’t why Serge 
had done what he had done. It was why Goldman Sachs had 
done what it had done. Why on earth call the FBI? Why exploit 
the ignorance of both the general public and the legal system 
about complex financial matters to punish this one little guy? 
Why must the spider always eat the fly? 

The financial insiders had many theories about this: that it 
was an accident; that Goldman had called the FBI in haste and 
then realized the truth, but lost control of the legal process; that 
in 2009 Goldman had been on hair-trigger alert to personnel 
losses in high-frequency trading, because they could see how 
much money would be made from it, and thought they could 
compete in the business. The jurors all had ideas about why 
what had happened had happened. One of the theories was more 
intriguing than the others. It had to do with the nature of a big 
Wall Street bank, and the way people who worked for it, at the 



intersection of technology and trading, got ahead. As one juror 
put it, “Every manager of a Wall Street tech group likes to have 
people believe that his guys are geniuses. Russians, whatever. 
His whole persona among his peers is that what he and his team 
do can’t be replicated. When people find out that ninety-five 
percent of their code is open source, it kills that perception. 
What the guy can’t say, when he gets told Serge has taken some- 
thing, is ‘it doesn’t matter what he took because it’s worse than 
what they’ll create on their own.’ So when the security people 
come to him and tell him about the downloads, he can’t say, ‘No 
big deal.’ And he can’t say, ‘I don’t know what he took.’ ” 

To put it another way: The process that ended with Serge 
Aleynikov sitting inside two holding facilities that housed dan- 
gerous offenders and then a federal prison may have started with 
the concern of some Goldman Sachs manager with his bonus. 
“Who is going to pull the fire alarm before they smell the fire?” 
asked the juror who had advanced this last theory. “It’s always 
the people who are politically motivated.” As he left dinner 
with Serge Aleynikov and walked down Wall Street, he thought 
about it some more. “I’m actually nauseous,” he said. “It makes 
me sick.” 

THE MYSTERY THE jury of Sergey Aleynikov’s peers had more trou- 
ble solving was Serge himself. He appeared, and perhaps even 
was, completely at peace with the world. Had you lined up the 
people at those two Wall Street dinners and asked the American 
public to vote for the man who had just lost his marriage, his 
home, his job, his life savings, and his reputation, Serge would 
have come dead last. At one point, one of the people at the table 
stopped the conversation about computer code and asked, “Why 



aren’t you angry?” Serge just smiled back at him. “No, really,” 
said the juror. “How do you stay so calm? I’d be fucking going 
crazy.” Serge smiled again. “But what does craziness give you?” 
he said. “What does negative demeanor give you as a person? It 
doesn’t give you anything. You know that something happened. 
Your life happened to go in that particular route. If you know 
that you’re innocent, know it. But at the same time you know 
you are in trouble and this is how it’s going to be.” To which he 
added, “To some extent I’m glad this happened to me. I think 
it strengthened my understanding of what living is all about.” 
At the end of his trial, when the original jury returned with its 
guilty verdict, Serge had turned to his lawyer, Kevin Marino, 
and said, “You know, it did not turn out the way we had hoped. 
But I have to say, it was a pretty good experience.” It was as if he 
were standing outside himself and taking in the situation as an 
observer. “I’ve never seen anything like it,” said Marino. 

In the comfort of the Wall Street cornucopia, that notion — that 
the hellish experience he’d been through had actually been good 
for him — was too weird to pursue, and the jurors had quickly 
returned to discussing computer code and high-frequency trad- 
ing. But Serge actually believed what he had said. Before his 
arrest — before he lost much of what he thought important in his 
life — he went through his days and nights in a certain state of 
mind: a bit self-absorbed, prone to anxiety and worry about his 
status in the world. “When I was arrested, I couldn’t sleep,” he 
said. “When I saw articles in the newspaper, I would tremble at 
the fear of losing my reputation. Now I just smile. 1 no longer 
panic. Or have panic ideas that something could go wrong.” By 
the time he was first sent to jail, his wife had left him, taking 
their three young daughters with her. He had no money and no 
one to turn to. “He didn’t have very close friends,” his fellow 



Russian emigre Masha Leder recalled. “He never did. He’s not a 
people person. He didn’t even have anyone to be power of attor- 
ney.” Out of a sense of Russian solidarity, and out of pity, she 
took the job — which meant, among other things, frequent trips 
to visit Serge in prison. “Every time I would come to visit him 
in jail, I would leave energized by him,” she said. “He radiated 
so much energy and positive emotions that it was like therapy 
for me to visit him. His eyes opened to how the world really is. 
And he started talking to people. For the first time! He would 
say: People in jail have the best stories. He could have considered 
himself a tragedy. And he didn’t.” 

By far the most difficult part of his experience was explain- 
ing what had happened to his children. When he was arrested, 
his daughters were five, three, and almost one. “I tried to put 
it in the most simple terms they would understand,” said Serge. 
“But the bottom line was I was apologizing for the fact that this 
had happened.” In jail he was allowed three hundred minutes 
a month on the phone — and for a long time the kids, when he 
called them, didn’t pick up on the other end. 

The holding facility in which Serge spent his first four months 
was violent, and essentially nonverbal, but he didn’t find it hard 
to stay out of trouble there. He even found people he could 
talk to, and enjoy talking to. When they moved him to the 
minimum-security prison at Fort Dix, in New Jersey, he was 
still in a room crammed with hundreds of other roommates, but 
he now had space to work. He remained in some physical dis- 
tress, mainly because he refused to eat meat. “His body, he had 
really bad times there,” said Masha Leder. “He lived on beans 
and rice. He was always hungry. I’d buy him these yogurts and 
he would gulp them down one after another.” His mind still 
worked fine, though, and a lifetime of programming in cube 



farms had left him with the ability to focus in prison conditions. 
A few months into Serge’s jail term, Masha Leder received a 
thick envelope from him. It contained roughly a hundred pages 
covered on both sides in Serge’s meticulous eight-point script. It 
was computer code — a solution to some high-frequency trading 
problem. Serge feared that if the prison guards found it, they 
wouldn’t understand it, decide that it was suspicious, and con- 
fiscate it. 

A year after he’d been sent away, the appeal of Serge Aleynikov 
was finally heard, by the Second Circuit Court of Appeals. The 
judgment was swift, unlike anything his lawyer, Kevin Marino, 
had seen in his career. Marino was by then working gratis for a 
client who was dead broke. The very day he made his argument, 
the judges ordered Serge released, on the grounds that the laws 
he stood accused of breaking did not actually apply to his case. 
At six in the morning on February 17, 2012, Serge received an 
email from Kevin Marino saying that he was to be freed. 

A few months later, Marino noticed that the government had 
failed to return Serge’s passport. Marino called and asked for 
it back. The passport never arrived; instead Serge, now stay- 
ing with friends in New Jersey, was arrested again and taken to 
jail. Once again, he had no idea what he was being arrested for, 
but this time neither did the police. The New Jersey cops who 
picked him up didn’t know the charges, only that he should be 
held without bail, as he was deemed a flight risk. His lawyer was 
just as perplexed. “When I got the call,” said Marino, “I thought 
it might have something to do with Serge’s child support.” It 
didn’t. A few days later, Manhattan district attorney Cyrus Vance 
sent out a press release to announce that the State of New York 
was charging Serge Aleynikov with “accessing and duplicating 
a complex proprietary and highly confidential computer source 



code owned by Goldman Sachs.” The press release went on to 
say that “ [t]his code is so highly confidential that it is known in 
the industry as the firm’s ‘secret sauce,’ ” and thanked Goldman 
Sachs for its cooperation. The prosecutor assigned to the case, 
Joanne Li, claimed that Serge was a flight risk and needed to be 
re -jailed immediately — which was strange, because Serge had 
gone to and returned from Russia between the time of his first 
arrest and his first jailing. (It was Li who soon fled the case— to 
a job at Citigroup.) 

Marino recognized the phrase “secret sauce.” It hadn’t come 
from “the industry” but from his opening statement in Serge’s 
first trial, when he mocked the prosecutors for treating Goldman’s 
code as if it were some “secret sauce.” Otherwise Serge’s re-arrest 
made no sense to him. To avoid double jeopardy, the Manhattan 
DA’s office had found new crimes with which to charge Serge 
for the same actions. But the sentencing guidelines for the new 
crimes meant that, even if he was convicted, it was very likely 
he wouldn’t have to return to jail. He’d already served time, for 
crimes the court ultimately determined he had not committed. 
Marino called Vance’s office. “They told me that they didn’t 
need him to be punished anymore, but they need him to be held 
accountable,” said Marino. “They want him to plead guilty and 
let him go on time served. I told them in the politest terms pos- 
sible that they can go fuck themselves. They ruined his life.” 

Oddly enough, they hadn’t. “Inside of me I was completely 
witnessing,” said Serge, about the night of his re-arrest. “There 
was no fear, no panic, no negativity.” His children had reat- 
tached themselves to him, and he had a new world of people to 
whom he felt close. He thought he was living his life as well as it 
had ever been lived. He’d even started a memoir, to explain what 
had happened to anyone who might be interested. He began: 



If the incarceration experience doesn’t break your spirit, it 
changes you in a way that you lose many fears. You begin to 
realize that your life is not ruled by your ego and ambition and 
that it can end any day at any time. So why worry? You learn 
that just like on the street, there is life in prison, and random 
people get there based on the jeopardy of the system. The pris- 
ons are filled by people who crossed the law, as well as by those 
who were incidentally and circumstantially picked and crushed 
by somebody else’s agenda. On the other hand, as a vivid ben- 
efit, you become very much independent of material property 
and learn to appreciate very simple pleasures in life such as the 
sunlight and morning breeze. 



F or at least a few members of the Women’s Adventure Club 
of Centre County, Pennsylvania, the weather was never 
much of an issue. The Women’s Adventure Club had been 
created by Lisa Wandel, an administrator at Penn State Uni- 
versity, after she realized that many women were afraid to hike 
alone in the woods. The club now had more than seven hundred 
members, and its sense of adventure had expanded far beyond 
a walk in the woods. Between them the four women who met 
me on their bicycles beside the Pennsylvania road had: learned 
the flying trapeze, swum the Chesapeake Bay, and won silver at 
the downhill mountain biking world championships; they had 
finished a road bike race called the Gran Fondo “Masochistic 
Metric,” a footrace called the Tough Mudder, and three separate 
twenty-four-hour-long mountain bike races; they had gradu- 
ated from race car driving school and made thirteen Polar Bear 
Plunges in some local river in the dead of winter. After studying 
the Women’s Adventure Club’s website, Ronan had said, “It’s a 



bunch of lunatic women who meet up and do dangerous shit; I 
got to get my wife into it.” 

In the bleak January light we pedaled onto Route 45 out of 
Boalsburg, Pennsylvania, heading east, along what was once the 
route for the stagecoach that ran from Philadelphia to Erie. It 
was nine in the morning, and still below freezing, with a stiff 
breeze lowering the windchill to eleven degrees. The views 
were of farms and fallow brown fields, and the road was empty 
except for the occasional pickup truck, roaring past us with real 
anger. “They hate bikers,” explained one of the women adven- 
turers mildly. “They try to see how close they can get.” 

The women rode this stretch of road every so often, and had 
noticed when the fiber-optic line was being laid beside it, back 
in 2010. From time to time one of the road’s two lanes was 
closed by the line’s construction crews. You’d see these motley 
queues of bikes, cars, pickup trucks, Amish horse-drawn carts, 
and farm equipment waiting for the tail end of the oncoming 
traffic. The crews trenched the ground between the paved road 
and the farms, making it difficult for the Amish in their wagons 
to get back to their homes — sometimes you’d see these Amish 
kids, the girls in their pretty purple dresses, hopping off the 
wagon and leaping over the trench. The members of the Wom- 
en’s Adventure Club had been told by a local government official 
that the fiber-optic line was a government project to provide 
high-speed Internet access to local colleges. Hearing that it was 
actually a private project to provide a 3-millisecond edge to 
high-frequency traders, they had some new questions about it. 
“How does a private line get access to a public right-of-way?” 
asked one. “I’m really curious to know that.” 



WE’RE IN A transition here. That’s what the Goldman Sachs peo- 
ple said when you asked them, in so many words, how they 
could have gone from bringing the wrath of U.S. prosecutors 
down upon Serge Aleynikov for emailing their high-frequency 
trading computer code to himself, to helping Brad Katsuyama 
change the U.S. stock market in ways that would render Gold- 
man’s high-frequency trading computer code worthless. 

There was a connection between Serge Aleynikov and 
Goldman’s behavior on December 19, 2013. The trial and the 
publicity that attended it caused a lot of people to think more 
rigorously about the value of Goldman Sachs’s high-frequency 
trading code. High-frequency trading had a winner-take-all 
aspect: The fastest predator took home the fattest prey. By 2013 
the people charged with determining Goldman’s stock market 
strategy had concluded that Goldman wasn’t very good at this 
new game, and that Goldman was unlikely ever to be very good 
at it. The high-frequency traders would always be faster than 
Goldman Sachs — or any other big Wall Street bank. The people 
who ran Goldman Sachs’s stock market department had come to 
understand that what Serge had taken wasn’t worth stealing — at 
least not by anyone whose chief need was speed. 

The trouble for any big Wall Street bank wasn’t simply that a 
big bureaucracy was ill-suited to keeping pace with rapid tech- 
nological change, but that the usual competitive advantages of a 
big Wall Street bank were of little use in high-frequency trad- 
ing. A big Wall Street bank’s biggest advantage was its access to 
vast amounts of cheap risk capital and, with that, its ability to 
survive the ups and downs of a risky business. That meant little 
when the business wasn’t risky and didn’t require much capital. 
High-frequency traders went home every night with no posi- 
tion in the stock market. They traded in the market the way card 



counters in a casino played blackjack: They played only when 
they had an edge. That’s why they were able to trade for five 
years without losing money on a single day. 

A big Wall Street bank really had only one advantage in an 
ever-faster financial market: first shot at its own customers’ stock 
market trades. So long as the customers remained inside the dark 
pool, and in the dark, the bank might profit at their expense. 
But even here the bank would never do the job as efficiently 
or thoroughly as a really good HFT. It was hard to resist the 
pressure to hand the prey over to the more skilled predator, to 
ensure that the kill was done quickly and discreetly, and then, 
after the kill, to join in the feast as a kind of junior partner — 
though more junior than partner. In the dark pool arbitrage IEX 
had witnessed, for instance, HFT captured about 85 percent of 
the gains, leaving the bank with just 15 percent. 

The new structure of the U.S. stock market had removed the big 
Wall Street banks from their historic, lucrative role as intermediary. 
At the same time it created, for any big bank, some unpleasant risks: 
that the customer would somehow figure out what was happening 
to his stock market orders. And that the technology might some- 
how go wrong. If the markets collapsed, or if another flash crash 
occurred, the high-frequency traders would not take 85 percent of 
the blame, or bear 85 percent of the costs of the inevitable lawsuits. 
The banks would bear the lion’s share of the blame and the costs. 
The relationship of the big Wall Street banks to the high-frequency 
traders, when you thought about it, was a bit like the relationship 
of the entire society to the big Wall Street banks. When things 
went well, the HFT guys took most of the gains; when things went 
badly, the HFT guys vanished and the banks took the losses. 

Goldman had figured all of this out — probably before the 
other big Wall Street banks, to judge from its treatment of IEX. 



By December 19, 2013, the people newly installed on top of 
Goldman Sachs’s stock market operations, Ron Morgan and 
Brian Levine, wanted to change the way the market worked. 
They were obviously sincere. They truly believed that the mar- 
ket at the heart of the world’s largest economy had grown too 
complex, and was likely to experience some catastrophic failure. 
But they also were trying to put an end to a game they could 
never win — or control. And so they’d flipped a switch, and sent 
lots of their customers’ stock market orders to IEX. When they 
did this they started a process that, if allowed to play out, would 
take billions from Wall Street and return it to investors. It would 
also create fairness. 

A big Wall Street bank was a complex environment. There 
were people inside Goldman Sachs less than pleased by what 
Levine and Morgan had done. And after December 19 the firm 
had retreated, just a little bit. It was hard even for Brad Kat- 
suyama to know why. Was it changing its collective mind? Had 
it underestimated the cost of being the first mover? Was it too 
much to ask Goldman Sachs to look up from short-term profit 
and study the landscape down the road? It was possible that even 
Goldman Sachs did not know the answers to those questions. 
Whatever the answers, something Brian Levine had said still 
made a lot of sense. “There will be a lot of resistance,” he’d said. 
“There will be a lot of resistance. Because a tremendous infra- 
structure has been built up around this.” 

It’s worth performing a Goldman Sachs-like cost-benefit anal- 
ysis of this infrastructure, from the point of view of the economy 
it is meant to serve. The benefit: Stock market prices adjust to 
new information a few milliseconds faster than they otherwise 
might. The costs make for a longer list. One obvious cost is the 
instability introduced into the system when its primary goal is 



no longer stability but speed. Another is the incalculable billions 
collected by financial intermediaries. That money is a tax on 
investment, paid for by the economy; and the more that produc- 
tive enterprise must pay for capital, the less productive enterprise 
there will be. Another cost, harder to measure, was the influence 
all this money exerted, not just on the political process but on 
people’s decisions about what to do with their lives. The more 
money to be made gaming the financial markets, the more peo- 
ple would decide they were put on earth to game the financial 
markets — and create romantic narratives to explain to themselves 
why a life spent gaming the financial markets is a purposeful life. 
And then there is maybe the greatest cost of all: Once very smart 
people are paid huge sums of money to exploit the flaws in the 
financial system, they have the spectacularly destructive incen- 
tive to screw the system up further, or to remain silent as they 
watch it being screwed up by others. 

The cost, in the end, is a tangled-up financial system. Untan- 
gling it requires acts of commercial heroism — and even then 
the fix might not work. There was simply too much more easy 
money to be made by elites if the system worked badly than if 
it worked well. The whole culture had to want to change. “We 
know how to cure this,” as Brad had put it. “It’s just a matter of 
whether the patient wants to be treated.” 

FOR A LONG stretch along the Spread Networks line, there was no 
happy place for a rider to stop. The road’s shoulder was narrow, 
and the cornfields beside it were planted with No Trespassing 
signs. Apart from the plastic soda bottle and the carcasses of deer 
killed by the speeding pickup trucks, and a shop or two, the 
landscape looked a lot like it once did from the Philadelphia- 



Erie stagecoach. The most insistent signs of modernity were the 
white poles with their bright orange domes, every few hundred 
yards, installed three and a half years earlier. After ten miles 
or so we found an open field without a sign and pulled over 
beside a white-and-orange pole. The poles stretched into the 
distance in both directions. An ambitious hiker or cyclist could 
follow them all the way to a building beside the Nasdaq stock 
exchange, in New Jersey; or, if he turned and headed west, to 
the Chicago Mercantile Exchange. 

Across the road was a local landmark: the Red Round Barn. 
One of the women repeated a rural legend, saying that the red 
barn had been built in the round so that mice had no corners in 
which to hide. “People don’t know how to live in a world that 
is transparent,” Brad Katsuyama had said, and mice were prob- 
ably no better at it. Beyond the barn was a mountain. On top 
of the mountain was a microwave tower — a string of them, in 
fact, perched on the mountains above the valley in which the 
line was buried. 

It takes roughly 8 milliseconds to send a signal from Chi- 
cago to New York and back by microwave signal, or about 4.5 
milliseconds less than to send it inside an optical fiber. When 
Spread Networks was laying its line, the conventional wisdom 
was that microwave could never replace fiber. It might be faster, 
but whatever was going on between New York and Chicago 
required huge amounts of complicated data to be sent back and 
forth, and a microwave signal couldn’t transmit nearly as much 
data as a signal in a fiber-optic cable. Microwave signals needed 
a direct line of sight to get to wherever they were going, with 
nothing in between. And microwave signals didn’t travel well in 
bad weather. 

But what if microwave technology improved? And what if the 



data essential for some high-frequency trader to gain an edge 
over investors in the market wasn’t actually all that complicated? 
And what if the tops of mountains afforded a direct line of sight 
between distant financial markets? 

The risks taken by high-frequency traders were not the 
usual risks taken by people who purport to sit in the middle of 
markets, buying from sellers and selling to buyers. They didn’t 
risk buying a bunch of shares in a falling stock, or selling a 
bunch of shares in a rising one. They were too skittish and well 
informed for that — with one obvious exception. They were all 
exposed to the risk that the entire stock market would move, 
by a lot. A big high-frequency trader might “make markets” 
in several thousand individual stocks in New Jersey. As the 
purpose of these buy and sell orders was not to buy and sell 
stock but to tease out market information from others, the 
orders would typically be tiny in each stock: 100 shares bid, 
100 shares offered. There was little risk in any individual case 
but great risk in the aggregate. If, say, some piece of bad news 
hit the market, and the entire stock market fell, it would take 
all the individual stocks with it. Any high-frequency traders 
who did not receive advance warning would be left owning 
100 shares each of several thousand different stocks they did 
not want to own, with big losses in each. 

But the U.S. stock market had an accidental beauty to it, from 
the point of view of a trader who wished to trade only when he 
had some edge. The big moves occurred first in the futures mar- 
ket in Chicago, before sweeping into the markets for individual 
stocks. If you were able to detect these moves, and warn your 
computers in New Jersey of price movements in Chicago, you 
could simply withdraw your bids for individual stocks before 
the market fully realized that it had fallen. That’s why it was so 



important for high-frequency traders to move information faster 
than everyone else from the futures exchange in Chicago to the 
stock markets in New Jersey: to flee the market before others. 
This race was run not just against ordinary investors, or even 
Wall Street banks, but also against other high-frequency traders. 
The first high-frequency trader to reach New Jersey with the 
news could sell 100 shares each in thousands of different stocks 
to the others. 

After some obligatory staring at the Red Round Barn, we 
jumped back on our bikes and continued. A few miles down 
the road, we turned onto the road leading to the summit of a 
mountain with a tower on top of it. The woman who had won 
the silver medal at the downhill mountain biking world cham- 
pionships sighed. “I like going down more than going up,” she 
said, then took off at speed, leaving everyone else behind. Soon 
I was watching the backs of female riders, climbing rapidly. It 
could have been worse: The Appalachians are mercifully old 
and worn. This particular mountain, once the size of a Swiss 
Alp, had been shrunken by half a billion years of bad weather. 
It was now almost beneath the dignity of the Women’s Adven- 
ture Club. 

It took maybe twenty minutes to puff to the top of the road, 
where the women adventurers stood waiting. From there we 
turned onto a smaller road leading into the woods, headed in the 
direction of the mountaintop. We rode through the woods for 
a few hundred yards until the road ended — or, rather, was bar- 
ricaded by a new metal gate. There we ditched our bikes, leapt 
over the signs warning of various dangers, and hiked onto a gravel 
path that continued to the mountaintop. The women didn’t think 
twice about any of this: To them it was just another adventure. A 
few minutes later the microwave tower came into view. 



“I climbed up one of these towers once,” one of the women 
said a bit wistfully. 

The tower was 180 feet high, with no ladder, and festooned 
with electrical equipment. “Why did you do that?” I asked. 

“I was pregnant and it was a lot of work,” she replied, as if that 
answered the question. 

“And that’s why your baby had seven toes!” hooted one of the 
other women, and they all laughed. 

If one of the women had hopped over the fence around the 
tower and climbed to the top, she would have had an unob- 
structed view of the next tower and, from there, the tower 
beyond. This was just one in a chain of thirty-eight towers that 
carried news of the direction of the stock market from Chicago 
to New Jersey: up or down; buy or sell; in or out. We walked 
around the site. The tower showed some signs of age. It could 
have been erected some time ago, for some other purpose. But 
the ancillary equipment— the generator, a concrete bunker to 
hold God knows what — was all shiny and new. The repeaters 
that amplify financial signals resembled kettle drums, bolted 
onto the side of the tower: These were also new. The speed 
with which they transmitted signals, and with which the com- 
puters on either end of the chain of towers turned the signals 
into financial actions, were still as difficult to comprehend as the 
forces of nature once had been. Anything said about them could 
be believed. People no longer are responsible for what happens in the 
market, because computers make all the decisions. And in the begin- 
ning God created the heaven and the earth. 

I noticed, before we left, a metal plate attached to the fence 
around the tower. On it was a Federal Communications Com- 
mission license number: 1215095. The number, along with an 
Internet connection, was enough to lead an inquisitive person to 



the story behind the tower. The application to use the tower to 
send a microwave signal had been filed in July 2012, and it had 
been filed by . . . well, it isn’t possible to keep any of this secret 
anymore. A day’s journey in cyberspace would lead anyone who 
wished to know it into another incredible but true Wall Street 
story, of hypocrisy and secrecy and the endless quest by human 
beings to gain a certain edge in an uncertain world. All that one 
needed to discover the truth about the tower was the desire to 
know it. 


T he U.S. financial system has experienced many changes 
since I first entered it, and one of them is in its relationship 
to any writer who attempts to figure out what’s going on 
inside of it. Wall Street firms — not just the big banks but all of 
them — have grown greatly more concerned than they were in 
the late 1980s with what some journalist might say about them. 
To judge only from their behavior, they have a lot more to fear. 
They are more likely than they once were to seek to shape any 
story told about them. At the same time, the people who work 
in these firms have grown more cynical about them, and more 
willing to reveal their inner workings, so long as their name 
is not attached to these revelations. As a result, I am unable to 
thank many of the people inside banks and high-frequency trad- 
ing firms and stock exchanges who spoke openly about them, 
and helped me to comprehend the seemingly incomprehensible. 
Some other people not mentioned in this book were impor- 



tant to its creation. Jacob Weisberg read an early draft and had 
shrewd things to say about it. At different times and in different 
ways, Dacher Keltner, Tabitha Soren, and Doug Stumpf listened 
to me drone on at length about what I was working on, and 
responded with thoughts that never would have occurred to me. 
Jaime Lalinde helped me, invaluably, in researching the case of 
Serge Aleynikov. I apologize to Ryan Harrington, at W. W. 
Norton, for sending him chasing around for illustrations that 
I thought might be useful but which turned out to be a dumb 
idea. He did it very well, though. 

Starling Lawrence has edited my books since I first started 
writing them, with his peculiar combination of encouragement 
and detachment. He edited this one, too, and I’ve never ben- 
efited so much from his unwillingness to allow me to enjoy 
even the briefest moment of self-satisfaction. The third member 
of our team, Janet Byrne, is the finest copy editor I have ever 
worked with. Many mornings her enthusiasm got me out of my 
bed, and many evenings her diligence prevented me from get- 
ting back into it. 

Finally, I’d like not only to thank the employees of IEX but 
also to list them by name, so one day people can look back 
and know them. They are: Lana Amer, Benjamin Aisen, Daniel 
Aisen, Joshua Blackburn, Donald Bohemian, James Cape, Fran- 
cis Chung, Adrian Facini, Stan Feldman, Brian Foley, Ramon 
Gonzalez, Bradley Katsuyama, Craig Katsuyama, Joe Kondel, 
Gerald Lam, Frank Lennox, Tara McKee, Rick Molakala, Tom 
O’Brien, Robert Park, Stefan Parker, Zoran Perkov, Eric Quin- 
lan, Ronan Ryan, Rob Salman, Prerak Sanghvi, Eric Schmid, 
John Schwall, Constantine Sokoloff, Beau Tateyama, Matt 
Trudeau, Larry Yu, Allen Zhang, and Billy Zhao. 

(continued from front flap) 

good for your blood pressure, because if 
you have any contact with the market, even 
a retirement account, this story is happening 
to you. But in the end, Flash Boys is an 
uplifting read. Here are people who have 
somehow preserved a moral sense in an envi- 
ronment where you don’t get paid for that; 
they have perceived an institutionalized 
injustice and are willing to go to war to fix it. 

MICHAEL LEWIS is the best-selling 
author of Liar’s Poker, Moneyball , The Blind 
Side, and The Big Short. He lives in Berkeley, 
California, with his wife and three children. 





praise for MICHAEL LE W I S 

“I read Michael Lewis for the same reason I watch Tiger Woods. I'll never play like 
that. But it’s good to be reminded every now and again what genius looks like.” 

— MALCOLM GLADWELL, New York Times Book Review 


“By the summer of 2013, the world’s financial markets were designed to maximize 
the number of collisions between ordinary investors and high-frequency traders 
at the expense of ordinary investors and for the benefit of high-frequency traders, 
exchanges, Wall Street banks, and online brokerage firms. Around those collisions 
an entire ecosystem had arisen.”